Continuous Monitoring of Turning Mobility and Its Association to Falls and Cognitive Function: A Pilot Study

Evaluating Postural Transition Movement Performance in Individuals with Essential Tremor via the Instrumented Timed Up and Go

Flexibility in performing various movements like standing, walking, and turning is crucial for navigating dynamic environments in daily life. Individuals with essential tremor often experience movement difficulties that can affect these postural transitions, limiting mobility and independence. Yet, little research has examined the performance of postural transitions in people with essential tremor. Therefore, we assessed postural transition performance using two versions of the timed up and go test: the standard version and a more complex water-carry version. We examined the total duration of the standard and water-carry timed up and go in 15 people with and 15 people without essential tremor. We also compared the time taken for each phase (sit-to-stand phase, straight-line walk phase, stand-to-sit phase) and the turning velocity between groups. Our findings revealed decreased performance across all phases of standard and water-carry timed up and go assessments. Further, both ET and non-ET groups exhibited reduced performance during the water-carry timed up and go compared to the standard timed up and go. Evaluating specific phases of the timed up and go offers valuable insights into functional movement performance in essential tremor, permitting more tailored therapeutic interventions to improve functional performance during activities of daily living.

Turning speed as a more responsive metric of age-related decline in mobility: A comparative study with gait speed

BACKGROUND

Navigating your environment requires both straight-line gait as well as turning. Gait speed normative values are well established and utilized in determining a person's functional status, however, it has limitations. This study sought to examine whether turning speed declines with age and how it compared to gait speed age-related decline.

METHODS

A secondary analysis was performed on 275 community dwelling adults between the ages of 18-88 that performed a timed walking test with an inertial measurement unit on their lumbar spine. Turning speed and walking speed were extracted for each participant. A series of mixed models were compared, and Akaike's Information Criterion was used to determine the best fit model between age and turning speed and age and gait speed.

FINDINGS

Turning speed and gait speed normative values were reported for each age decade. A linear model with a random intercept of "Condition" was used to assess the relationship between age and turning speed. The results indicated a significant negative relationship between age and turning speed (B = -0.66, p < 0.001). A spline-fit model determined a significant negative relationship between age and gait speed after the age of 65 (B = -0.0097, p = 0.002). The effect of age on gait speed before age 65 was not significant.

INTERPRETATION

Turning speed significantly declines with age in a linear fashion while gait speed begins to decline after age 65. Turning speed may be more responsive to age than gait speed. More research is needed to determine if the decline in turning speed with age is associated with a decline in function.

Dual-task turn velocity - a novel digital biomarker for mild cognitive impairment and dementia

Background

Disorders associated with cognitive impairment impose a significant burden on both families and society. Previous studies have indicated that gait characteristics under dual-task as reliable markers of early cognitive impairment. Therefore, digital gait detection has great potential for future cognitive screening. However, research on digital biomarkers based on smart devices to identify cognitive impairment remains limited. The aim of this study is to explore digital gait biomarkers by utilizing intelligent wearable devices for discriminating mild cognitive impairment and dementia.

Methods

This study included 122 subjects (age: 74.7 ± 7.7 years) diagnosed with normal cognition (NC, n = 38), mild cognitive impairment (MCI, n = 42), or dementia (n = 42). All subjects underwent comprehensive neuropsychological assessments and cranial Magnetic Resonance Imaging (MRI). Gait parameters were collected using validated wearable devices in both single-task and dual-task (DT). We analyzed the ability of gait variables to predict MCI and dementia, and examined the correlations between specific DT-gait parameters and sub-cognitive functions as well as hippocampal atrophy.

Results

Our results demonstrated that dual-task could significantly improve the ability to predict cognitive impairment based on gait parameters such as gait speed (GS) and stride length (SL). Additionally, we discovered that turn velocity (TV and DT-TV) can be a valuable novel digital marker for predicting MCI and dementia, for identifying MCI (DT-TV: AUC = 0.801, sensitivity 0.738, specificity 0.842), and dementia (DT-TV: AUC = 0.923, sensitivity 0.857, specificity 0.842). The correlation analysis and linear regression analysis revealed a robust association between DT-TV and memory function, as well as the hippocampus atrophy.

Conclusion

This study presents a novel finding that DT-TV could accurately identify varying degrees of cognitive impairment. DT-TV is strongly correlated with memory function and hippocampus shrinkage, suggests that it can accurately reflect changes in cognitive function. Therefore, DT-TV could serve as a novel and effective digital biomarker for discriminating cognitive impairment.

Quantifying Turning Tasks With Wearable Sensors: A Reliability Assessment

OBJECTIVE

The aim of this study was to establish the test-retest reliability of metrics obtained from wearable inertial sensors that reflect turning performance during tasks designed to imitate various turns in daily activity.

METHODS

Seventy-one adults who were healthy completed 3 turning tasks: a 1-minute walk along a 6-m walkway, a modified Illinois Agility Test (mIAT), and a complex turning course (CTC). Peak axial turning and rotational velocity (yaw angular velocity) were extracted from wearable inertial sensors on the head, trunk, and lumbar spine. Intraclass correlation coefficients (ICCs) were established to assess the test-retest reliability of average peak turning speed for each task. Lap time was collected for reliability analysis as well.

RESULTS

Turning speed across all tasks demonstrated good to excellent reliability, with the highest reliability noted for the CTC (45-degree turns: ICC = 0.73-0.81; 90-degree turns: ICC = 0.71-0.83; and 135-degree turns: ICC = 0.72-0.80). The reliability of turning speed during 180-degree turns from the 1-minute walk was consistent across all body segments (ICC = 0.74-0.76). mIAT reliability ranged from fair to excellent (end turns: ICC = 0.52-0.72; mid turns: ICC = 0.50-0.56; and slalom turns: ICC = 0.66-0.84). The CTC average lap time demonstrated good test-retest reliability (ICC = 0.69), and the mIAT average lap time test-retest reliability was excellent (ICC = 0.91).

CONCLUSION

Turning speed measured by inertial sensors is a reliable outcome across a variety of ecologically valid turning tasks that can be easily tested in a clinical environment.

IMPACT

Turning performance is a reliable and important measure that should be included in clinical assessments and clinical trials.

Cognitive status is associated with performance of manual wheelchair skills in hospitalized older adults

PURPOSE

To examine the relationship between manual wheelchair skills and cognitive function in hospitalized older adults.

METHODS

The observational study included older adults who used a manual wheelchair following hip/knee surgery. Participants underwent a series of tests to evaluate manual wheelchair skills and cognitive performance. Four items appearing on the Wheelchair Skills Test: brake handling (locking/unlocking), a 10-metre forward roll, a 2-metre backward roll and rotating in place, were used to evaluate manual wheelchair skills. Cognitive function was evaluated by the Montreal Cognitive Assessment (MoCA), Trail Making Test (TMT), the Clock Drawing Test, and the Loewenstein Occupational Therapy Cognitive Assessment. The relationship between wheelchair skills and cognitive scores was assessed by a series of univariate linear regression analyses.

RESULTS

Fifty older adults, aged 65-85, participated in the study. The MoCA-7 (orientation) explained 19.3% of the variance related to the turn in place wheelchair skill, 18.8% of the variance related to the two-metre backwards roll and 31.9% of the variance related to the 10-metre forward roll. The addition of gender (to the MoCA-7) increased the explained variance related to the 10-metre forward roll and turn in place skills to 38.5% and 28.5%, respectively. As for the brakes handling skill test, gender explained 18.3% of the variance. The addition of the CDT (to gender) increased the explained variance for the brakes handling skill to 31.4%.

CONCLUSIONS

Because cognitive impairments negatively affect the performance of wheelchair skills, rehabilitation therapists may need to adjust wheelchair mobility training methods for cognitively impaired older adults.Implication for rehabilitationGiven the prevalence of older adults with cognitive impairments who use manual wheelchairs, it is critical to better understand the relationship between cognition and wheelchair skills.Poor results reported on the cognitive tests, specifically, visual attention and orientation, were found to be associated with poor performance of four manual wheelchair skills.Rehabilitation therapists should consider the cognitive status of older adults when teaching manual wheelchair skills, specifically in new users. Future studies should examine whether a customized preparation program, enhancing visuospatial orientation, can benefit manual wheelchair control in older adults.

Recovery of turning speed in patients after vestibular schwannoma resection

BACKGROUND

Individuals after a vestibular schwannoma resection (VSR) experience significant vestibular symptoms that can be provoked with turning. Vestibular rehabilitation assists in recovery of function and symptom relief, however turning response is unknown.

OBJECTIVE

Examine peak turning speed response to surgery and rehabilitation.

METHODS

Eight participants with a vestibular schwannoma (PwVS) and five healthy controls (HC) participated in this study. Peak turning speed (PTS) was captured with inertial measurement units (IMU) at the head and/or trunk during turning tasks at a pre-operative, post-operative and post-treatment assessment. Vestibular rehabilitation was provided twice weekly for six weeks. Linear mixed models were used to assess change in PTS across time points.

RESULTS

PwVS performed slower PTS than HC prior to surgery. PTS was significantly slower post-operatively compared to pre-operative during walking with head turns (B = -61.03, p = 0.004), two-minute walk test (B = -37.33, p = 0.015), 360° turn (B range from 50.05 to -57.4, p < 0.05) and complex turning course (CTC) at the trunk (B = -18.63, p = 0.009). Post-treatment PTS was significantly faster than pre-operative during CTC at the head (B = 18.46, p = 0.014) and trunk (B = 15.99, p = 0.023).

CONCLUSION

PwVS may have turning deficits prior to surgical resection. PTS was significantly affected post-operatively, however improved with rehabilitation.

Identifying trajectories and predictors of chemotherapy-induced peripheral neuropathy symptoms, physical functioning, and falls across treatment and recovery in adults treated with neurotoxic chemotherapy: the PATTERN observational study protocol (NCT05790538)

BACKGROUND

Chemotherapy-induced peripheral neuropathy (CIPN) is a debilitating and dose-limiting side effect of systemic cancer therapy. In many cancer survivors, CIPN persists after treatment ends and is associated with functional impairments, abnormal gait patterns, falls, and diminished quality of life. However, little is known regarding which patients are most likely to develop CIPN symptoms that impair mobility and increase fall risk, when this risk develops, or the optimal timing of early intervention efforts to mitigate the impact of CIPN on functioning and fall risk. This study will address these knowledge gaps by (1) characterizing trajectories of symptoms, functioning, and falls before, during, and after treatment in adults prescribed neurotoxic chemotherapy for cancer; and (2) determining the simplest set of predictors for identifying individuals at risk for CIPN-related functional decline and falls.

METHODS

We will enroll 200 participants into a prospective, observational study before initiating chemotherapy and up to 1 year after completing chemotherapy. Eligible participants are aged 40-85 years, diagnosed with stage I-III cancer, and scheduled to receive neurotoxic chemotherapy. We perform objective assessments of vibratory and touch sensation (biothesiometry, tuning fork, monofilament tests), standing and dynamic balance (quiet stance, Timed-Up-and-Go tests), and upper and lower extremity strength (handgrip dynamometry, 5-time repeated chair stand test) in the clinic at baseline, every 4-6 weeks during chemotherapy, and quarterly for 1 year post-chemotherapy. Participants wear devices that passively and continuously measure daily gait quality and physical activity for 1 week after each objective assessment and self-report symptoms (CIPN, insomnia, fatigue, dizziness, pain, cognition, anxiety, and depressive symptoms) and falls via weekly electronic surveys. We will use structural equation modeling, including growth mixture modeling, to examine patterns in trajectories of changes in symptoms, functioning, and falls associated with neurotoxic chemotherapy and then search for distinct risk profiles for CIPN.

DISCUSSION

Identifying simple, early predictors of functional decline and fall risk in adults with cancer receiving neurotoxic chemotherapy will help identify individuals who would benefit from early and targeted interventions to prevent CIPN-related falls and disability.

TRIAL REGISTRATION

This study was retrospectively registered with ClinicalTrials.gov (NCT05790538) on 3/30/2023.

A pilot study comparing prosthetic to sound limb gait mechanics during a turning task in people with transtibial amputation

BACKGROUND

Observational gait analysis is frequently used by clinicians to subjectively assess straight walking but is not often used to examine turning. Interlimb comparisons of phase- specific turning biomechanics in people with unilateral lower limb amputation has not previously been documented.

METHODS

A retrospective examination of gait kinematics and kinetics from five participants with unilateral transtibial amputation was performed. Data were collected during 90° step and spin turns capturing three distinct turning steps. Gait metrics of interest included: total turn time, stance time, peak knee flexion angle during Pre-Swing and Initial Swing gait phases, peak hip flexion and extension, ground reaction impulse, and whole body angular momentum. Statistical comparisons were made based on turn type between sound and prosthetic limbs.

FINDINGS

During the three turn steps (approach, apex, depart), participants spent significantly more time (P < 0.01) on their sound limb compared to their prosthetic limb regardless of turn type. Additionally, the prosthetic limb hip and knee exhibited more flexion (P < 0.05) during the apex step of turns, and whole body angular momentum was higher when the sound limb was used during the apex step of a turn (P < 0.05).

INTERPRETATION

This descriptive study offers the first phase-specific quantification of turning biomechanics in people with lower limb amputation. Results indicate that people with unilateral transtibial amputation spend more time on and experience higher impulses through their sound compared to their prosthetic limb during 90° turns, and that the prosthetic limb is performing differently than the sound limb, potentially increasing risks of injury or falls.

The effect of mobility-related anxiety on walking across the lifespan: a virtual reality simulation study

Older adults who report a fear of falling are more likely to subsequently fall, yet, some gait anxiety-related alterations may protect balance. We examined the effect of age on walking in anxiety-inducing virtual reality (VR) settings. We predicted a high elevation-related postural threat would impair gait in older age, and differences in cognitive and physical function would relate to the observed effects. Altogether, 24 adults (age (y) = 49.2 (18.7), 13 women) walked on a 2.2-m walkway at self-selected and fast speeds at low (ground) and high (15 m) VR elevation. Self-reported cognitive and somatic anxiety and mental effort were greater at high elevations (all p < 0.001), but age- and speed-related effects were not observed. At high VR elevations, participants walked slower, took shorter steps, and reduced turning speed (all p < 0.001). Significant interactions with age in gait speed and step length showed that relatively older adults walked slower (β = - 0.05, p = 0.024) and took shorter steps (β = - 0.05, p = 0.001) at self-selected speeds at high compared to low elevation settings. The effect of Age on gait speed and step length disappeared between self-selected and fast speeds and at high elevation. At self-selected speeds, older adults took shorter and slower steps at high elevation without changing step width, suggesting that in threatening settings relatively older people change gait parameters to promote stability. At fast speeds, older adults walked like relatively younger adults (or young adults walked like older adults) supporting the notion that people opt to walk faster in a way that still protects balance and stability in threatening settings.

Gait-phase specific transverse-plane momenta generation during pre-planned and late-cued 90 degree turns while walking

Turning while walking is ubiquitous and requires linear and angular momenta generation to redirect the body's trajectory and rotate towards the new direction of travel. This study examined strategies that healthy young adults used during each gait phase to generate transverse-plane momenta during pre-planned and late-cued 90° turns. During leftward turns, we expected that momenta would be generated most during the gait phases known to generate leftward linear and angular momenta during straight line gait. We found distinct roles of gait phases towards generating momenta during turns that partially supported our hypotheses. Supporting one hypothesis, the change in transverse-plane angular momentum and average moment were greater during double support with the left foot in front vs. other gait phases. Also, the change in leftward linear momentum and average leftward force were greater during right single support vs. other gait phases during straight-line gait and late-cued turns. However, during pre-planned turns, the average leftward force was not significantly greater during right single support vs. other gait phases. Overall, transverse-plane angular momentum generation during turns is similar to its generation during straight-line gait, suggesting that healthy young adults can leverage momenta control strategies used during straight-line gait during turns.

The Instrumented Stand and Walk (ISAW) test to predict falls in older men

Objective measures of balance and gait have the potential to improve prediction of future fallers because balance and gait impairments are common precursors. We used the Instrumented Stand and Walk Test (ISAW) with wearable, inertial sensors to maximize the domains of balance and gait evaluated in a short test. We hypothesized that ISAW objective measures across a variety of gait and balance domains would improve fall prediction beyond history of falls and better than gait speed or dual-task cost on gait-speed. We recruited 214 high-functioning older men (mean 82 years), of whom 91 participants (42.5%) had one or more falls in the 12 months following the ISAW test. The ISAW test involved 30 s of stance followed by a 7-m walk, turn, and return. We examined regression models for falling using 17 ISAW metrics, with and without age and fall history, and characterize top-performing models by AUC and metrics included. The ISAW test improved distinguishing between future fallers and non-fallers compared to age and history of falls, alone (AUC improved from 0.69 to 0.75). Models with 1 ISAW metric usually included a postural sway measure, models with 2 ISAW measures included a turning measure, models with 3 ISAW measures included a gait variability measure, and models with 4 or 5 measures added a gait initiation measure. Gait speed and dual-task cost did not distinguish between fallers and non-fallers in this high-functioning cohort. The best fall-prediction models support the notion that older people may fall due to a variety of balance and gait impairments.

A scoping review of neurodegenerative manifestations in explainable digital phenotyping

Neurologists nowadays no longer view neurodegenerative diseases, like Parkinson's and Alzheimer's disease, as single entities, but rather as a spectrum of multifaceted symptoms with heterogeneous progression courses and treatment responses. The definition of the naturalistic behavioral repertoire of early neurodegenerative manifestations is still elusive, impeding early diagnosis and intervention. Central to this view is the role of artificial intelligence (AI) in reinforcing the depth of phenotypic information, thereby supporting the paradigm shift to precision medicine and personalized healthcare. This suggestion advocates the definition of disease subtypes in a new biomarker-supported nosology framework, yet without empirical consensus on standardization, reliability and interpretability. Although the well-defined neurodegenerative processes, linked to a triad of motor and non-motor preclinical symptoms, are detected by clinical intuition, we undertake an unbiased data-driven approach to identify different patterns of neuropathology distribution based on the naturalistic behavior data inherent to populations in-the-wild. We appraise the role of remote technologies in the definition of digital phenotyping specific to brain-, body- and social-level neurodegenerative subtle symptoms, emphasizing inter- and intra-patient variability powered by deep learning. As such, the present review endeavors to exploit digital technologies and AI to create disease-specific phenotypic explanations, facilitating the understanding of neurodegenerative diseases as "bio-psycho-social" conditions. Not only does this translational effort within explainable digital phenotyping foster the understanding of disease-induced traits, but it also enhances diagnostic and, eventually, treatment personalization.

Gait and turning characteristics from daily life increase ability to predict future falls in people with Parkinson's disease

Objectives

To investigate if digital measures of gait (walking and turning) collected passively over a week of daily activities in people with Parkinson's disease (PD) increases the discriminative ability to predict future falls compared to fall history alone.

Methods

We recruited 34 individuals with PD (17 with history of falls and 17 non-fallers), age: 68 ± 6 years, MDS-UPDRS III ON: 31 ± 9. Participants were classified as fallers (at least one fall) or non-fallers based on self-reported falls in past 6 months. Eighty digital measures of gait were derived from 3 inertial sensors (Opal® V2 System) placed on the feet and lower back for a week of passive gait monitoring. Logistic regression employing a "best subsets selection strategy" was used to find combinations of measures that discriminated future fallers from non-fallers, and the Area Under Curve (AUC). Participants were followed via email every 2 weeks over the year after the study for self-reported falls.

Results

Twenty-five subjects reported falls in the follow-up year. Quantity of gait and turning measures (e.g., number of gait bouts and turns per hour) were similar in future fallers and non-fallers. The AUC to discriminate future fallers from non-fallers using fall history alone was 0.77 (95% CI: [0.50-1.00]). In contrast, the highest AUC for gait and turning digital measures with 4 combinations was 0.94 [0.84-1.00]. From the top 10 models (all AUCs>0.90) via the best subsets strategy, the most consistently selected measures were variability of toe-out angle of the foot (9 out of 10), pitch angle of the foot during mid-swing (8 out of 10), and peak turn velocity (7 out of 10).

Conclusions

These findings highlight the importance of considering precise digital measures, captured via sensors strategically placed on the feet and low back, to quantify several different aspects of gait (walking and turning) during daily life to improve the classification of future fallers in PD.

Effect of Levodopa and Environmental Setting on Gait and Turning Digital Markers Related to Falls in People with Parkinson's Disease

Background

It is unknown whether medication status (off and on levodopa) or laboratory versus home settings plays a role in discriminating fallers and non-fallers in people with Parkinson's disease (PD).

Objectives

To investigate which specific digital gait and turning measures, obtained with body-worn sensors, best discriminated fallers from non-fallers with PD in the clinic and during daily life.

Methods

We recruited 34 subjects with PD (17 fallers and 17 non-fallers based on the past 6 month's falls). Subjects wore three inertial sensors attached to both feet and the lumbar region in the laboratory for a 3-minute walking task (both off and on levodopa) and during daily life activities for a week. We derived 24 digital (18 gait and 6 turn) measures from the 3-minute walk and from daily life.

Results

In clinic, none of the gait and turning measures collected during on levodopa state were significantly different between fallers and non-fallers. In contrast, digital measures collected in the off levodopa state were significantly different between groups, (average turn velocity, average number of steps to complete a turn, and variability of gait speed, P < 0.03). During daily life, the variability of average turn velocity (P = 0.023) was significantly different in fallers than non-fallers. Last, the average number of steps to complete a turn was significantly correlated with the patient-reported outcomes.

Conclusions

Digital measures of turning, but not gait, were different in fallers compared to non-fallers with PD, in the laboratory when off medication and during a daily life.

Effect of Lower Limb vs. Abdominal Compression on Mobility in Orthostatic Hypotension: A Single-Blinded, Randomized, Controlled, Cross-Over Pilot Study in Parkinson's Disease

BACKGROUND

Orthostatic hypotension (OH) in Parkinson's disease (PD) is frequent and associated with impairments in quality of life and reduced activities of daily living. Abdominal binders (AB) and compression stockings (CS) have been shown to be effective non-pharmacological treatment options.

OBJECTIVE

Here, we investigate the effect of AB versus CS on physical activity using a digital mobility outcome (sit to stand [STS] frequency) collected in the usual environment as a primary endpoint.

METHODS

We enrolled 16 PD patients with at least moderate symptomatic OH. In a randomized, single-blinded, controlled, crossover design, participants were assessed without OH treatment over 1 week (baseline), then were given AB or CS for 1 week and subsequently switched to the other treatment arm. The primary outcome was the number of real-life STS movements per hour as assessed with a lower back sensor. Secondary outcomes included real-life STS duration, mean/systolic/diastolic blood pressure drop (BPD), orthostatic hypotension questionnaire (OHQ), PD quality of life (PDQ-39), autonomic symptoms (SCOPA-AUT), non-motor symptoms (NMSS), MDS-UPDRS, and activities of daily living (ADL/iADL).

RESULTS

Real-life STS frequency on CS was 4.4±4.1 per hour compared with 3.6±2.2 on AB and 3.6±1.8 without treatment (p = 1.0). Concerning the secondary outcomes, NMSS showed significant improvement with CS and AB. OHQ and SCOPA-AUT improved significantly with AB but not CS, and mean BPD drop worsened with CS but not AB. Mean STS duration, PDQ-39, MDS-UPDRS, ADL, and iADL did not significantly change.

CONCLUSION

Both AB and CS therapies do not lead to a significant change of physical activity in PD patients with at least moderate symptomatic OH. Secondary results speak for an effect of both therapies concerning non-motor symptoms, with superiority of AB therapy over CS therapy.

Egocentric vision-based detection of surfaces: towards context-aware free-living digital biomarkers for gait and fall risk assessment

Background

Falls in older adults are a critical public health problem. As a means to assess fall risks, free-living digital biomarkers (FLDBs), including spatiotemporal gait measures, drawn from wearable inertial measurement unit (IMU) data have been investigated to identify those at high risk. Although gait-related FLDBs can be impacted by intrinsic (e.g., gait impairment) and/or environmental (e.g., walking surfaces) factors, their respective impacts have not been differentiated by the majority of free-living fall risk assessment methods. This may lead to the ambiguous interpretation of the subsequent FLDBs, and therefore, less precise intervention strategies to prevent falls.

Methods

With the aim of improving the interpretability of gait-related FLDBs and investigating the impact of environment on older adults’ gait, a vision-based framework was proposed to automatically detect the most common level walking surfaces. Using a belt-mounted camera and IMUs worn by fallers and non-fallers (mean age 73.6 yrs), a unique dataset (i.e., Multimodal Ambulatory Gait and Fall Risk Assessment in the Wild (MAGFRA-W)) was acquired. The frames and image patches attributed to nine participants’ gait were annotated: (a) outdoor terrains: pavement (asphalt, cement, outdoor bricks/tiles), gravel, grass/foliage, soil, snow/slush; and (b) indoor terrains: high-friction materials (e.g., carpet, laminated floor), wood, and tiles. A series of ConvNets were developed: EgoPlaceNet categorizes frames into indoor and outdoor; and EgoTerrainNet (with outdoor and indoor versions) detects the enclosed terrain type in patches. To improve the framework’s generalizability, an independent training dataset with 9,424 samples was curated from different databases including GTOS and MINC-2500, and used for pretrained models’ (e.g., MobileNetV2) fine-tuning.

Results

EgoPlaceNet detected outdoor and indoor scenes in MAGFRA-W with 97.36$$\%$$ % and 95.59$$\%$$ % (leave-one-subject-out) accuracies, respectively. EgoTerrainNet-Indoor and -Outdoor achieved high detection accuracies for pavement (87.63$$\%$$ % ), foliage (91.24$$\%$$ % ), gravel (95.12$$\%$$ % ), and high-friction materials (95.02$$\%$$ % ), which indicate the models’ high generalizabiliy.

Conclusions

Encouraging results suggest that the integration of wearable cameras and deep learning approaches can provide objective contextual information in an automated manner, towards context-aware FLDBs for gait and fall risk assessment in the wild.

Suitability of a Low-Cost Wearable Sensor to Assess Turning in Healthy Adults

Background: Turning is a complex measure of gait that accounts for over 50% of daily steps. Traditionally, turning has been measured in a research grade laboratory setting, however, there is demand for a low-cost and portable solution to measure turning using wearable technology. This study aimed to determine the suitability of a low-cost inertial sensor-based device (AX6, Axivity) to assess turning, by simultaneously capturing and comparing to a turn algorithm output from a previously validated reference inertial sensor-based device (Opal), in healthy young adults. Methodology: Thirty participants (aged 23.9 ± 4.89 years) completed the following turning protocol wearing the AX6 and reference device: a turn course, a two-minute walk (including 180° turns) and turning in place, alternating 360° turn right and left. Both devices were attached at the lumbar spine, one Opal via a belt, and the AX6 via double sided tape attached directly to the skin. Turning measures included number of turns, average turn duration, angle, velocity, and jerk. Results: Agreement between the outcomes from the AX6 and reference device was good to excellent for all turn characteristics (all ICCs > 0.850) during the turning 360° task. There was good agreement for all turn characteristics (all ICCs > 0.800) during the two-minute walk task, except for moderate agreement for turn angle (ICC 0.683). Agreement for turn outcomes was moderate to good during the turns course (ICCs range; 0.580 to 0.870). Conclusions: A low-cost wearable sensor, AX6, can be a suitable and fit-for-purpose device when used with validated algorithms for assessment of turning outcomes, particularly during continuous turning tasks. Future work needs to determine the suitability and validity of turning in aging and clinical cohorts within low-resource settings.

TURN-IT: a novel turning intervention program to improve quality of turning in daily life in people with Parkinson's disease

BACKGROUND

People with Parkinson's disease (PD) have a high fall rate and many falls are associated with turns. Despite this, there is minimal research on effects of rehabilitation on the quality of turns. Further, quantifying turns in the home may have broader implications since rehabilitation of turns would ideally improve turning in real world mobility.

METHODS

Sixty people with PD and a history of falls will be randomized to receive either a novel TURNing InTervention (TURN-IT) or no intervention (control group). The TURN-IT group will be seen for 6 weeks (18 visits) for an individualized, progressive program that is based on the specific constraints of turning in PD. Wearable sensors will be used to measure 7 days of mobility, including turns, before and after intervention or control period. In addition, blinded assessments of gait, mobility and turns will occur before and after intervention for both groups and falls will be monitored for twelve months post intervention with bimonthly email questionnaires.

DISCUSSION

This study has the potential to change how we rehabilitate and assess turning in people with PD and falls. There are several novel aspects to our study including a comprehensive turning-focused intervention that is tailored to the underlying constraints that impair turning in people with PD. Further, our outcome measure of turning quality during 7 days of daily life is novel and has implications for determining real-life changes after rehabilitation. The ultimate goal of this rehabilitation intervention is to improve how patients turn in daily life and to reduce falls.

TRIALS REGISTRATION

This protocol is registered at clinicaltrials.gov; #NCT04897256; https://clinicaltrials.gov/ct2/show/NCT04897256?term=Horak&cond=Parkinson+Disease&draw=2&rank=4 .

Objective monitoring of functional recovery after total knee and hip arthroplasty using sensor-derived gait measures

Background

Inertial sensors hold the promise to objectively measure functional recovery after total knee (TKA) and hip arthroplasty (THA), but their value in addition to patient-reported outcome measures (PROMs) has yet to be demonstrated. This study investigated recovery of gait after TKA and THA using inertial sensors, and compared results to recovery of self-reported scores of pain and function.

Methods

PROMs and gait parameters were assessed before and at two and fifteen months after TKA (n = 24) and THA (n = 24). Gait parameters were compared with healthy individuals (n = 27) of similar age. Gait data were collected using inertial sensors on the feet, lower back, and trunk. Participants walked for two minutes back and forth over a 6m walkway with 180° turns. PROMs were obtained using the Knee Injury and Osteoarthritis Outcome Scores and Hip Disability and Osteoarthritis Outcome Score.

Results

Gait parameters recovered to the level of healthy controls after both TKA and THA. Early improvements were found in gait-related trunk kinematics, while spatiotemporal gait parameters mainly improved between two and fifteen months after TKA and THA. Compared to the large and early improvements found in of PROMs, these gait parameters showed a different trajectory, with a marked discordance between the outcome of both methods at two months post-operatively.

Conclusion

Sensor-derived gait parameters were responsive to TKA and THA, showing different recovery trajectories for spatiotemporal gait parameters and gait-related trunk kinematics. Fifteen months after TKA and THA, there were no remaining gait differences with respect to healthy controls. Given the discordance in recovery trajectories between gait parameters and PROMs, sensor-derived gait parameters seem to carry relevant information for evaluation of physical function that is not captured by self-reported scores.

Visual Cues for Turning in Parkinson's Disease

Turning is a common impairment of mobility in people with Parkinson’s disease (PD), which increases freezing of gait (FoG) episodes and has implications for falls risk. Visual cues have been shown to improve general gait characteristics in PD. However, the effects of visual cues on turning deficits in PD remains unclear. We aimed to (i) compare the response of turning performance while walking (180° and 360° turns) to visual cues in people with PD with and without FoG; and (ii) examine the relationship between FoG severity and response to visual cues during turning. This exploratory interventional study measured turning while walking in 43 participants with PD (22 with self-reported FoG) and 20 controls using an inertial sensor placed at the fifth lumbar vertebrae region. Participants walked straight and performed 180° and 360° turns midway through a 10 m walk, which was done with and without visual cues (starred pattern). The turn duration and velocity response to visual cues were assessed using linear mixed effects models. People with FoG turned slower and longer than people with PD without FoG and controls (group effect: p < 0.001). Visual cues reduced the velocity of turning 180° across all groups and reduced the velocity of turning 360° in people with PD without FoG and controls. FoG severity was not significantly associated with response to visual cues during turning. Findings suggest that visual cueing can modify turning during walking in PD, with response influenced by FoG status and turn amplitude. Slower turning in response to visual cueing may indicate a more cautious and/or attention-driven turning pattern. This study contributes to our understanding of the influence that cues can have on turning performance in PD, particularly in freezers, and will aid in their therapeutic application.

A Comparison of Turning Kinematics at Different Amplitudes during Standing Turns between Older and Younger Adults

It is well-established that processes involving changing direction or turning in which either or both standing and walking turns are utilized involve coordination of the whole-body and stepping characteristics. However, the turn context and whole-body coordination have not been fully explored during different turning amplitudes. For these reasons, this present study aimed to determine the effects of turning amplitude on whole-body coordination. The findings from this study can be utilized to inform the rationale behind fall prevention factors and to help design an exercise strategy to address issues related to amplitude of turning in older adults. Twenty healthy older and twenty healthy younger adults were asked to complete standing turns on level ground using three randomly selected amplitudes, 90°, 135° and 180°, at their self-selected turn speed. Turning kinematics and stepping variables were recorded using Inertial Measurement Units. Analysis of the data was carried out using Mixed Model Analysis of Variance with two factors (2 groups × 3 turning amplitudes) and further post hoc pairwise analysis to examine differences between factors. There were significant interaction effects (p < 0.05) between the groups and turning amplitudes for step duration and turn speed. Further analysis using Repeated Measure Analysis of Variance tests determined a main effect of amplitude on step duration and turn speed within each group. Furthermore, post hoc pairwise comparisons revealed that the step duration and turn speed increased significantly (p < 0.001) with all increases in turning amplitude in both groups. In addition, significant main effects for group and amplitudes were seen for onset latency of movement for the head, thorax, pelvis, and feet, and for peak head–thorax and peak head–pelvis angular separations and stepping characteristics, which all increased with turn amplitude and showed differences between groups. These results suggest that large amplitude turns result in a change in turning and stepping kinematics. Therefore, when assessing the turning characteristics of older adults or those in frail populations, the turning amplitude should be taken into account during turning, and could be gradually increased to challenge motor control as part of exercise falls prevention strategies.

Troubleshooting Gait Disturbances in Parkinson's Disease With Deep Brain Stimulation

Deep brain stimulation (DBS) of the subthalamic nucleus or the globus pallidus is an established treatment for Parkinson's disease (PD) that yields a marked and lasting improvement of motor symptoms. Yet, DBS benefit on gait disturbances in PD is still debated and can be a source of dissatisfaction and poor quality of life. Gait disturbances in PD encompass a variety of clinical manifestations and rely on different pathophysiological bases. While gait disturbances arising years after DBS surgery can be related to disease progression, early impairment of gait may be secondary to treatable causes and benefits from DBS reprogramming. In this review, we tackle the issue of gait disturbances in PD patients with DBS by discussing their neurophysiological basis, providing a detailed clinical characterization, and proposing a pragmatic programming approach to support their management.

Detection of balance disorders using rotations around vertical axis and an artificial neural network

Vestibular impairments affect patients' movements and can result in difficulties with daily life activities. The main aim of this study is to answer the question whether a simple and short test such as rotation about a vertical axis can be an objective method of assessing balance dysfunction in patients with unilateral vestibular impairments. A 360˚ rotation test was performed using six MediPost devices. The analysis was performed in three ways: (1) the analytical approach based only on data from one sensor; (2) the analytical approach based on data from six sensors; (3) the artificial neural network (ANN) approach based on data from six sensors. For approaches 1 and 2 best results were obtained using maximum angular velocities (MAV) of rotation and rotation duration (RD), while approach 3 used 11 different features. The following sensitivities and specificities were achieved: for approach 1: MAV—80% and 60%, RD—69% and 74%; for approach 2: 61% and 85% and RD—74% and 56%; for approach 3: 88% and 84%. The ANN-based six-sensor approach revealed the best sensitivity and specificity among parameters studied, however one-sensor approach might be a simple screening test used e.g. for rehabilitation purposes.

Early Notice Pointer, an IoT-like Platform for Point-of-Care Feet and Body Balance Screening

Improper foot biomechanics associated with uneven bodyweight distribution contribute to impaired balance and fall risks. There is a need to complete the panel of commercially available devices for the self-measurement of BMI, fat, muscle, bone, weight, and hydration with one that measures weight-shifting at home as a pre-specialist assessment system. This paper reports the development of the Early Notice Pointer (ENP), a user-friendly screening device based on weighing scale technology. The ENP is designed to be used at home to provide a graphic indication and customised and evidence-based foot and posture triage. The device electronically detects and maps the bodyweight and distinct load distributions on the main areas of the feet: forefoot and rearfoot. The developed platform also presents features that assess the user's balance, and the results are displayed as a simple numerical report and map. The technology supports data display on mobile phones and accommodates multiple measurements for monitoring. Therefore, the evaluation could be done at non-specialist and professional levels. The system has been tested to validate its accuracy, precision, and consistency. A parallel study to describe the frequency of arch types and metatarsal pressure in young adults (1034 healthy subjects) was conducted to explain the importance of self-monitoring at home for better prevention of foot arch- and posture-related conditions. The results showed the potential of the newly created platform as a screening device ready to be wirelessly connected with mobile phones and the internet for remote and personalised identification and monitoring of foot- and body balance-related conditions. The real-time interpretation of the reported physiological parameters opens new avenues toward IoT-like on-body monitoring of human physiological signals through easy-to-use devices on flexible substrates for specific versatility.

Head and Trunk Kinematics during Activities of Daily Living with and without Mechanical Restriction of Cervical Motion

Alterations in head and trunk kinematics during activities of daily living can be difficult to recognize and quantify with visual observation. Incorporating wearable sensors allows for accurate and measurable assessment of movement. The aim of this study was to determine the ability of wearable sensors and data processing algorithms to discern motion restrictions during activities of daily living. Accelerometer data was collected with wearable sensors from 10 healthy adults (age 39.5 ± 12.47) as they performed daily living simulated tasks: coin pick up (pitch plane task), don/doff jacket (yaw plane task), self-paced community ambulation task [CAT] (pitch and yaw plane task) without and with a rigid cervical collar. Paired t-tests were used to discern differences between non-restricted (no collared) performance and restricted (collared) performance of tasks. Significant differences in head rotational velocity (jacket p = 0.03, CAT-pitch p < 0.001, CAT-yaw p < 0.001), head rotational amplitude (coin p = 0.03, CAT-pitch p < 0.001, CAT-yaw p < 0.001), trunk rotational amplitude (jacket p = 0.01, CAT-yaw p = 0.005), and head−trunk coupling (jacket p = 0.007, CAT-yaw p = 0.003) were captured by wearable sensors between the two conditions. Alterations in turning movement were detected at the head and trunk during daily living tasks. These results support the ecological validity of using wearable sensors to quantify movement alterations during real-world scenarios.

High Specificity of Single Inertial Sensor-Supplemented Timed Up and Go Test for Assessing Fall Risk in Elderly Nursing Home Residents

The Timed Up and Go test (TUG) is commonly used to estimate the fall risk in the elderly. Several ways to improve the predictive accuracy of TUG (cameras, multiple sensors, other clinical tests) have already been proposed. Here, we added a single wearable inertial measurement unit (IMU) to capture the residents’ body center-of-mass kinematics in view of improving TUG’s predictive accuracy. The aim is to find out which kinematic variables and residents’ characteristics are relevant for distinguishing faller from non-faller patients. Data were collected in 73 nursing home residents with the IMU placed on the lower back. Acceleration and angular velocity time series were analyzed during different subtasks of the TUG. Multiple logistic regressions showed that total time required, maximum angular velocity at the first half-turn, gender, and use of a walking aid were the parameters leading to the best predictive abilities of fall risk. The predictive accuracy of the proposed new test, called i + TUG, reached a value of 74.0%, with a specificity of 95.9% and a sensitivity of 29.2%. By adding a single wearable IMU to TUG, an accurate and highly specific test is therefore obtained. This method is quick, easy to perform and inexpensive. We recommend to integrate it into daily clinical practice in nursing homes.

Association Between Turning Mobility and Cognitive Function in Chronic Poststroke

Turning difficulties are common in patients with stroke. The detrimental effects of dual tasks on turning indicate a correlation between turning and cognition. Cognitive impairment is prevalent after stroke, and stroke patients with mild cognitive impairment had a poorer turning performance than did stroke patients with intact cognitive abilities. Therefore, we investigated the association between turning mobility and cognitive function in patients with chronic poststroke. Ninety patients with chronic stroke (>6 months post-stroke) were recruited. Angular velocity was assessed using wearable sensors during 180° walking turns and 360° turning on the spot from both sides. Global cognition and distinct cognitive domains were assessed using the Mini-Mental State Examination. In patients with stroke, turning mobility was significantly associated with global cognitive function and distinct cognitive domains, such as visuospatial ability and language. The balance function and lower limbs strength were mediators of the association between cognition and turning. The association highlights the complexity of the turning movement and dynamic motor and cognitive coordination necessary to safely complete a turn. However, our findings should be regarded as preliminary, and a thorough neuropsychological assessment to provide a valid description of distinct cognitive domains is required.

Differences in walking-to-turning characteristics between older adult fallers and nonfallers: a prospective and observational study using wearable inertial sensors

Wearable inertial sensors have gradually been used as an objective technology for biomechanical assessments of both healthy and pathological movement patterns. This paper used foot-worn sensors for characterizing the spatiotemporal characteristics of walking and turning between older fallers and nonfallers. Thirty community-dwelling older fallers and 30 older nonfallers performed 10-m straight walking, turned 180° around a cone, and then walked 10-m back to the starting point. Specific algorithms were used to measure spatiotemporal gait (double support phase of the gait cycle, swing width, and minimal toe clearance) and turning parameters (turn duration and turn steps) using two foot-worn Physiolog inertial sensor system. The researchers directly exported data as reported by the system. Our findings indicated that older fallers showed 26.58% longer time (P = 0.036) and 13.21% more steps (P = 0.038) compared to nonfallers during turning. However, both groups decreased their walking velocity (both P < 0.001), increased double support (both P = 0.001), and increased the swing width (both P = 0.001) during the transition from walking to turning. The older nonfallers additionally increased toe clearance (P = 0.001). Compared with the fallers, the older nonfallers showed a larger change in the swing width (P = 0.025) and toe clearance (P = 0.025) in walking to turning. Older fallers may adopt a cautionary strategy while turning to reduce the risk of falls. Wearable sensors can provide the temporospatial characteristics of turning and reveal significant differences by fall status, indicating the potential of turning measures as possible markers for identifying those at fall risk.

Test–retest reliability for performance-based outcome measures among individuals with arthrogryposis multiplex congenita

Background

Most individuals with arthrogryposis multiplex congenita, a rare condition characterized by joint contractures in ≥ 2 body regions, have foot and ankle involvement leading to compromised gait and balance. The purpose of this study was to establish between-days, test–retest reliability for performance-based outcome measures evaluating gait and balance, i.e., the 10-m Walk Test, Figure-of-8 Walk Test, 360-degree Turn Test, and modified Four Square Step Test, among adolescents and adults with arthrogryposis multiplex congenita.

Methods

This reliability study included ambulatory participants, aged 10 to 50 years, with a medical diagnosis of arthrogryposis multiplex congenita. Participants completed performance-based measures, in a randomized order, on two separate occasions. Intraclass correlation coefficients with 95% confidence intervals and minimal detectable changes at the 90% and 95% confidence level were calculated.

Results

Participants included 38 community-ambulators with a median of 13 out of 14 upper and lower joint regions affected. Intraclass correlation coefficient point estimates and 95% confidence intervals ranged from .85-.97 and .70-.98, respectively. Minimal detectable changes were 10 to 39% of sample means and were largest for the modified Four Square Step Test.

Conclusions

Among individuals with arthrogryposis, gait speed per the 10-m Walk Test, as well as non-linear walking and dynamic balance assessment per the Figure-of-8 Walk and 360 Degree Turn Tests, have adequate test–retest reliability enabling evaluation of individual patient changes. Changes in groups of ambulatory individuals with arthrogryposis multiplex congenita may be reliably evaluated with all of the studied outcome measures.

Clinical Disease Severity Mediates the Relationship between Stride Length and Speed and the Risk of Falling in Parkinson’s Disease

The shuffling gait with slowed speed and reduced stride length has been considered classic clinical features in idiopathic Parkinson’s disease (PD), and the risk of falling increases as the disease progresses. This raises the possibility that clinical disease severity might mediate the relationship between stride length and speed and the risk of falling in patients with PD. Sixty-one patients with PD patients underwent the clinical scores as well as quantitative biomechanical measures during walking cycles before and after dopamine replacement therapy. Mediation analysis tests whether the direct effect of an independent variable (stride length and speed) on a dependent variable (three-step fall prediction model score) can be explained by the indirect influence of the mediating variable (Unified Parkinson’s Disease Rating Scale (UPDRS) total scores). The results demonstrate that decreased stride length, straight walking speed, and turning speed is associated with increased three-step fall prediction model score (r = −0.583, p < 0.0001, r = −0.519, p < 0.0001, and r = −0.462, p < 0.0001, respectively). We further discovered that UPDRS total scores value is negatively correlated with stride length, straight walking, and turning speed (r = −0.651, p < 0.0001, r = −0.555, p < 0.0001, and r = −0.372, p = 0.005, respectively) but positively correlated with the fall prediction model score value (r = 0.527, p < 0.0001). Further mediation analysis shows that the UPDRS total score values serve as mediators between lower stride length, straight walking, and turning speed and higher fall prediction model score values. Our results highlighted the relationship among stride length and speed, clinical disease severity, and risk of falling. As decreased stride length and speed are hallmarks of falls, monitoring the changes of quantitative biomechanical measures along with the use of wearable technology in a longitudinal study can provide a scientific basis for pharmacology, rehabilitation programs, and selecting high-risk candidates for surgical treatment to reduce future fall risk.

Surrogates for rigidity and PIGD MDS-UPDRS subscores using wearable sensors

BACKGROUND

Telemedicine has the advantage of expanding access to care for patients with Parkinson's Disease (PD). However, rigidity and postural instability in PD are difficult to measure remotely, and are important measures of functional impairment and fall risk.

RESEARCH QUESTION

Can measures from wearable sensors be used as future surrogates for the MDS-UPDRS rigidity and Postural Instability and Gait Difficulty (PIGD) subscores?

METHODS

Thirty-one individuals with mild to moderate PD wore 3 inertial sensors at home for one week to measure quantity and quality of gait and turning in daily life. Separately, we performed a clinical assessment and balance characterization of postural sway with the same wearable sensors in the laboratory (On medication). We then first performed a traditional correlation analysis between clinical scores and objective measures of gait and balance followed by multivariable linear regression employing a best subset selection strategy.

RESULTS

The number of walking bouts and turns correlated significantly with the rigidity subscore, while the number of turns, foot pitch angle, and sway area while standing correlated significantly with the PIGD subscore (p < 0.05). The multivariable linear regression showed that rigidity subscore was best predicted by the number of walking bouts while the PIGD subscore was best predicted by a combination of number of walking bouts, gait speed, and postural sway.

SIGNIFICANCE

The correlation between objective sensor data and MDS-UPDRS rigidity and PIGD scores paves the way for future larger studies that evaluate use of objective sensor data to supplement remote MDS-UPDRS assessment.

Digital Biomarkers in Living Labs for Vulnerable and Susceptible Individuals: An Integrative Literature Review

PURPOSE

The study aimed to identify which digital biomarkers are collected and which specific devices are used according to vulnerable and susceptible individual characteristics in a living-lab setting.

MATERIALS AND METHODS

A literature search, screening, and appraisal process was implemented using the Web of Science, Pubmed, and Embase databases. The search query included a combination of terms related to "digital biomarkers," "devices that collect digital biomarkers," and "vulnerable and susceptible groups." After the screening and appraisal process, a total of 37 relevant articles were obtained.

RESULTS

In elderly people, the main digital biomarkers measured were values related to physical activity. Most of the studies used sensors. The articles targeting children aimed to predict diseases, and most of them used devices that are simple and can induce some interest, such as wearable device-based smart toys. In those who were disabled, digital biomarkers that measured location-based movement for the purpose of diagnosing disabilities were widely used, and most were measured by easy-to-use devices that did not require detailed explanations. In the disadvantaged, digital biomarkers related to health promotion were measured, and various wearable devices, such as smart bands and headbands were used depending on the purpose and target.

CONCLUSION

As the digital biomarkers and devices that collect them vary depending on the characteristics of study subjects, researchers should pay attention not only to the purpose of the study but also the characteristics of study subjects when collecting and analyzing digital biomarkers from living labs.

Intercepting Dementia: Awareness and Innovation as Key Tools

Dementia is a common feature of several age-related brain diseases, leading to a progressive cognitive decline. Due to a growing aging rate, dementia-related disorders currently affect around 50 million people worldwide and by 2050 this number is expected to reach 150 million. Additionally to patients, these neurodegenerative pathologies have a strong impact on family members, caretakers, and other health professionals, therefore representing a public health burden that in 2020 accounted for over 1 trillion USD and is projected to nearly double in the next decade. To overcome this devastating condition, many organizations and collaborative networks sustain that only a complete understanding of dementia in its different characteristics can drive the scientific community towards the development of effective therapeutic approaches aiming at preventing its onset and halting its progression.In this work, we discuss two topics that represent fundamental resources in fighting dementia: (i) the importance of raising awareness about this condition to avoid stigma and gauging investment; and (ii) the introduction of novel screening measures to prevent and potentially revert cognitive decline. Finally, we discern how knowledge-based advocacy will help the rollout of clinical trials and the development of novel and timely pharmacological interventions.

Recent Developments in Privacy-Preserving Mining of Clinical Data

With the dramatic increases in both the capability to collect personal data and the capability to analyze large amounts of data, increasingly sophisticated and personal insights are being drawn. These insights are valuable for clinical applications but also open up possibilities for identification and abuse of personal information. In this paper, we survey recent research on classical methods of privacy-preserving data mining. Looking at dominant techniques and recent innovations to them, we examine the applicability of these methods to the privacy-preserving analysis of clinical data. We also discuss promising directions for future research in this area.

The Effects of Different Types of Dual Tasking on Balance in Healthy Older Adults

Numerous of our daily activities are performed within multitask or dual task conditions. These conditions involve the interaction of perceptual and motor processes involved in postural control. Age-related changes may negatively impact cognition and balance control. Studies identifying changes related to dual-task actions in older people are need. This study aimed to determine the effects of different types of dual-tasking on the balance control of healthy older adults. The sample included 36 community-living older adults, performing two tests—a sway test and a timed up-and-go test—in three conditions: (a) single motor task; (b) dual motor task; and (c) dual motor task with cognitive demands. Cognitive processes (dual-task and cognition) affected static balance, increasing amplitude (p < 0.001) and frequency (p < 0.001) of the center of mass displacements. Dynamic balance revealed significant differences between the single motor condition and the other two conditions during gait phases (p < 0.001). The effect of dual-tasking in older adults suggests that cognitive processes are a main cause of increased variability in balance and gait when under an automatic control. During sit-to-stand, turning, and turn-to-sit movements under dual-tasking, the perceptive information becomes the most important focus of attention, while any cognitive task becomes secondary.

Performance and Characteristics of Wearable Sensor Systems Discriminating and Classifying Older Adults According to Fall Risk: A Systematic Review

Sensor-based fall risk assessment (SFRA) utilizes wearable sensors for monitoring individuals’ motions in fall risk assessment tasks. Previous SFRA reviews recommend methodological improvements to better support the use of SFRA in clinical practice. This systematic review aimed to investigate the existing evidence of SFRA (discriminative capability, classification performance) and methodological factors (study design, samples, sensor features, and model validation) contributing to the risk of bias. The review was conducted according to recommended guidelines and 33 of 389 screened records were eligible for inclusion. Evidence of SFRA was identified: several sensor features and three classification models differed significantly between groups with different fall risk (mostly fallers/non-fallers). Moreover, classification performance corresponding the AUCs of at least 0.74 and/or accuracies of at least 84% were obtained from sensor features in six studies and from classification models in seven studies. Specificity was at least as high as sensitivity among studies reporting both values. Insufficient use of prospective design, small sample size, low in-sample inclusion of participants with elevated fall risk, high amounts and low degree of consensus in used features, and limited use of recommended model validation methods were identified in the included studies. Hence, future SFRA research should further reduce risk of bias by continuously improving methodology.

Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review

BACKGROUND

Higher age and cognitive impairment are associated with a higher risk of falling. Wearable sensor technology may be useful in objectively assessing motor fall risk factors to improve physical exercise interventions for fall prevention. This systematic review aims at providing an updated overview of the current research on wearable sensors for fall risk assessment in older adults with or without cognitive impairment. Therefore, we addressed two specific research questions: 1) Can wearable sensors provide accurate data on motor performance that may be used to assess risk of falling, e.g., by distinguishing between faller and non-faller in a sample of older adults with or without cognitive impairment?; and 2) Which practical recommendations can be given for the application of sensor-based fall risk assessment in individuals with CI? A systematic literature search (July 2019, update July 2020) was conducted using PubMed, Scopus and Web of Science databases. Community-based studies or studies conducted in a geriatric setting that examine fall risk factors in older adults (aged ≥60 years) with or without cognitive impairment were included. Predefined inclusion criteria yielded 16 cross-sectional, 10 prospective and 2 studies with a mixed design.

RESULTS

Overall, sensor-based data was mainly collected during walking tests in a lab setting. The main sensor location was the lower back to provide wearing comfort and avoid disturbance of participants. The most accurate fall risk classification model included data from sit-to-walk and walk-to-sit transitions collected over three days of daily life (mean accuracy = 88.0%). Nine out of 28 included studies revealed information about sensor use in older adults with possible cognitive impairment, but classification models performed slightly worse than those for older adults without cognitive impairment (mean accuracy = 79.0%).

CONCLUSION

Fall risk assessment using wearable sensors is feasible in older adults regardless of their cognitive status. Accuracy may vary depending on sensor location, sensor attachment and type of assessment chosen for the recording of sensor data. More research on the use of sensors for objective fall risk assessment in older adults is needed, particularly in older adults with cognitive impairment.

TRIAL REGISTRATION

This systematic review is registered in PROSPERO ( CRD42020171118 ).

Clinical assessment of gait and functional mobility in Italian healthy and cognitively impaired older persons using wearable inertial sensors

AIM

The main purpose of the present study was to verify the feasibility of wearable inertial sensors (IMUs) in a clinical setting to screen gait and functional mobility in Italian older persons. In particular, we intended to verify the capability of IMUs to discriminate individuals with and without cognitive impairments and assess the existence of significant correlations between mobility parameters extracted by processing trunk accelerations and cognitive status.

METHODS

This is a cross-sectional study performed on 213 adults aged over 65 years (mean age 77.0 ± 5.4; 62% female) who underwent cognitive assessment (through Addenbrooke's Cognitive Examination Revised, ACE-R) instrumental gait analysis and the Timed Up and Go (TUG) test carried out using a wearable IMU located in the lower back.

RESULTS

Individuals with cognitive impairments exhibit a peculiar gait pattern, characterized by significant reduction of speed (- 34% vs. healthy individuals), stride length (- 28%), cadence (- 9%), and increase in double support duration (+ 11%). Slight, but significant changes in stance and swing phase duration were also detected. Poorer performances in presence of cognitive impairment were observed in terms of functional mobility as overall and sub-phase TUG times resulted significantly higher with respect to healthy individuals (overall time, + 38%, sub-phases times ranging from + 22 to + 34%), although with some difference associated with age. The severity of mobility alterations was found moderately to strongly correlated with the ACE-R score (Spearman's rho = 0.58 vs. gait speed, 0.54 vs. stride length, 0.66 vs. overall TUG time).

CONCLUSION

The findings obtained in the present study suggest that wearable IMUs appear to be an effective solution for the clinical assessment of mobility parameters of older persons screened for cognitive impairments within a clinical setting. They may represent a useful tool for the clinician in verifying the effectiveness of interventions to alleviate the impact of mobility limitations on daily life in cognitively impaired individuals.

XGBoost based machine learning approach to predict the risk of fall in older adults using gait outcomes

This study aimed to identify the optimal features of gait parameters to predict the fall risk level in older adults. The study included 746 older adults (age: 63–89 years). Gait tests (20 m walkway) included speed modification (slower, preferred, and faster-walking) while wearing the inertial measurement unit sensors embedded in the shoe-type data loggers on both outsoles. A metric was defined to classify the fall risks, determined based on a set of questions determining the history of falls and fear of falls. The extreme gradient boosting (XGBoost) model was built from gait features to predict the factor affecting the risk of falls. Moreover, the definition of the fall levels was classified into high- and low-risk groups. At all speeds, three gait features were identified with the XGBoost (stride length, walking speed, and stance phase) that accurately classified the fall risk levels. The model accuracy in classifying fall risk levels ranged between 67–70% with 43–53% sensitivity and 77–84% specificity. Thus, we identified the optimal gait features for accurate fall risk level classification in older adults. The XGBoost model could inspire future works on fall prevention and the fall-risk assessment potential through the gait analysis of older adults.

Basic Spatiotemporal Gait Variables of Young and Older Healthy Volunteers Walking Along a Novel Figure-of-8 Path

Background: Locomotion along curved trajectories requires fine coordination among body segments. Elderly people may adopt a cautious attitude when steering. A simple, expeditious, patient-friendly walking protocol can be a tool to help clinicians. We evaluated the feasibility of a procedure based upon a newly designed Figure-of-eight (nFo8) path and an easy measurement operation. Methods: Sixty healthy volunteers, aged from 20 to 86 years, walked three times at self-selected speed along a 20 m linear (LIN) and the 20 m nFo8 path. Number of steps, mean speed and walk ratio (step length/cadence) were collected. Data were analysed for the entire cohort and for the groups aged 20-45, 46-65, and >65 years. Results: There was no difference in mean LIN walking speed between the two younger groups but the oldest was slower. During nFo8, all groups were slower (about 16%) than during LIN. Cadence was not different across groups but lower during nFo8 in each group. Step length was about 8% shorter in the two younger groups and 14% shorter in the oldest during nFo8 compared to LIN. Walk ratio was the smallest in the oldest group for both LIN and nFo8. Conclusions: A complex nFo8 walking path, with fast and easy measurement of a simple set of variables, detects significant differences with moderate and large effects in gait variables in people >65 years. This challenging trajectory is more revealing than LIN. Further studies are needed to develop a quick clinical tool for assessment of gait conditions or outcome of rehabilitative treatments.

Turning assessment for discrimination of frailty syndrome among community-dwelling older adults

BACKGROUND

Frailty is a common geriatric syndrome and is characterized by decreased physiological reserve and increased vulnerability towards adverse health outcomes including falls. Turning is a challenging task and is reported to be one of the daily activities that leads to falling in older populations.

RESEARCH QUESTION

Does 180° walking turns and 360° turning on the spot differ among frail, pre-frail, and non-frail older adults? Can 180° walking turns and 360° turning on the spot cutoffs discriminate older adults with frailty from those without?

METHODS

A cross-sectional study was conducted on community-dwelling older adults aged over 65 years. Frailty was assessed using Fried's phenotype method, and turning tasks were measured by inertial sensors. The turn duration (s) and angular velocity (°/s) were recorded for analysis.

RESULTS

In total, 109 participants were enrolled including 50 pre-frail and 12 frail individuals. Frail older adults took significantly longer and had slower angular velocities to complete the 180° and 360° turning than did either pre-frail (p = 0.002 and p < 0.001, respectively) or non-frail (p = 0.03 and p < 0.001, respectively) older adults. Cutoff times of 2.45 and 3.46 s were found to best discriminate frail people from those without frailty in both the 180° (sensitivity 83.3 %, specificity 71.1 %, area under the receiver operating characteristic curve (AUC) 0.796) and 360° (sensitivity 91.7 %, specificity 74.2 %, AUC 0.857) turn tasks.

SIGNIFICANCE

Older individuals with frailty syndrome had difficulty turning as evidenced by a longer turning duration and a slower angular velocity. The turn duration could be a potential biomarker of frailty in older populations. Assessing the turning performance can facilitate early detection of the onset of frailty and inform early prevention and rehabilitation interventions in clinical practice.

Fusing Ambient and Mobile Sensor Features Into a Behaviorome for Predicting Clinical Health Scores

Advances in machine learning and low-cost, ubiquitous sensors offer a practical method for understanding the predictive relationship between behavior and health. In this study, we analyze this relationship by building a behaviorome, or set of digital behavior markers, from a fusion of data collected from ambient and wearable sensors. We then use the behaviorome to predict clinical scores for a sample of n = 21 participants based on continuous data collected from smart homes and smartwatches and automatically labeled with corresponding activity and location types. To further investigate the relationship between domains, including participant demographics, self-report and external observation-based health scores, and behavior markers, we propose a joint inference technique that improves predictive performance for these types of high-dimensional spaces. For our participant sample, we observe correlations ranging from small to large for the clinical scores. We also observe an improvement in predictive performance when multiple sensor modalities are used and when joint inference is employed.

Comparison of 360° Turn Cycles among Individuals after Stroke and Healthy Older Adults

Stroke survivors are at high risk of falling during turning. The kinematics of performing a 360° turn have not been fully analyzed among individuals after stroke. Quantitative differences in the parameters of turning between healthy older adults and those after stroke could provide detailed information on turning ability among these groups. The purpose of the current study was to characterize differences between healthy older adults and adults after stroke in 360° turn kinematics. Fourteen individuals with chronic stroke (mean age: 69 ± 8.4 years) and 14 healthy older adults (mean age: 74 ± 8.7 years) performed three trials of 360° turning. Kinematics data were collected using 26 reflective markers at several body landmarks. This new method for quantifying turning revealed that stroke significantly affected the number of turn cycles, number of single support (SS) critical phases, and critical time. In some cases, falls among individuals with stroke may be related to the combination of impaired movement patterns and the complexity of tasks such as turning. Understanding turning kinematics can inform clinical interventions targeting improvements in turning ability and consequently, fall risk reduction in individuals after stroke.

Detection of Wandering Behaviors Using a Body-Worn Inertial Sensor in Patients With Cognitive Impairment: A Feasibility Study

Patients with Alzheimer's disease (AD) and AD related dementias (ADRD) often experience spatial disorientation that can lead to wandering behavior, characterized by aimless or purposeless movement. Wandering behavior has been associated with falls, caregiver burden, and nursing home placement. Despite the substantial clinical consequences of wandering, there is currently no standardized approach to objectively quantify wandering behavior. In this pilot feasibility study, we used a lightweight inertial sensor to examine mobility characteristics of a small group of 12 older adults with ADRD and mild cognitive impairment in their homes. Specifically, we evaluated their compliance with wearing a sensor for a minimum of 4 days. We also examined the ability of the sensor to measure turning frequency and direction changes, given that frequent turns and direction changes during walking have been observed in patients who wander. We found that all patients were able to wear the sensor yielding quantitative turn data including number of turns over time, mean turn duration, mean peak turn speed, and mean turn angle. We found that wanderers make more frequent, quicker turns compared to non-wanderers, which is consistent with pacing or lapping behavior. This study provides preliminary evidence that continuous monitoring in patients with dementia is feasible using a wearable sensor. More studies are needed to explore if objective measures of turning behaviors collected using inertial sensors can be used to identify wandering behavior.

Independent and sensitive gait parameters for objective evaluation in knee and hip osteoarthritis using wearable sensors

Background

Although it is well-established that osteoarthritis (OA) impairs daily-life gait, objective gait assessments are not part of routine clinical evaluation. Wearable inertial sensors provide an easily accessible and fast way to routinely evaluate gait quality in clinical settings. However, during these assessments, more complex and meaningful aspects of daily-life gait, including turning, dual-task performance, and upper body motion, are often overlooked. The aim of this study was therefore to investigate turning, dual-task performance, and upper body motion in individuals with knee or hip OA in addition to more commonly assessed spatiotemporal gait parameters using wearable sensors.

Methods

Gait was compared between individuals with unilateral knee (n = 25) or hip OA (n = 26) scheduled for joint replacement, and healthy controls (n = 27). For 2 min, participants walked back and forth along a 6-m trajectory making 180° turns, with and without a secondary cognitive task. Gait parameters were collected using 4 inertial measurement units on the feet and trunk. To test if dual-task gait, turning, and upper body motion had added value above spatiotemporal parameters, a factor analysis was conducted. Effect sizes were computed as standardized mean difference between OA groups and healthy controls to identify parameters from these gait domains that were sensitive to knee or hip OA.

Results

Four independent domains of gait were obtained: speed-spatial, speed-temporal, dual-task cost, and upper body motion. Turning parameters constituted a gait domain together with cadence. From the domains that were obtained, stride length (speed-spatial) and cadence (speed-temporal) had the strongest effect sizes for both knee and hip OA. Upper body motion (lumbar sagittal range of motion), showed a strong effect size when comparing hip OA with healthy controls. Parameters reflecting dual-task cost were not sensitive to knee or hip OA.

Conclusions

Besides more commonly reported spatiotemporal parameters, only upper body motion provided non-redundant and sensitive parameters representing gait adaptations in individuals with hip OA. Turning parameters were sensitive to knee and hip OA, but were not independent from speed-related gait parameters. Dual-task parameters had limited additional value for evaluating gait in knee and hip OA, although dual-task cost constituted a separate gait domain. Future steps should include testing responsiveness of these gait domains to interventions aiming to improve mobility.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-021-04074-2.

Fall risk assessment in the wild: A critical examination of wearable sensor use in free-living conditions

BACKGROUND

Despite advances in laboratory-based supervised fall risk assessment methods (FRAs), falls still remain a major public health problem. This can be due to the alteration of behavior in laboratory due to the awareness of being observed (i.e., Hawthorne effect), the multifactorial complex etiology of falls, and our limited understanding of human behaviour in natural environments, or in the' wild'. To address these imitations, a growing body of literature has focused on free-living wearable-sensor-based FRAs. The objective of this narrative literature review is to discuss papers investigating natural data collected by wearable sensors for a duration of at least 24 h to identify fall-prone older adults.

METHODS

Databases (Scopus, PubMed and Google Scholar) were searched for studies based on a rigorous search strategy.

RESULTS

Twenty-four journal papers were selected, in which inertial sensors were the only wearable system employed for FRA in the wild. Gait was the most-investigated activity; but sitting, standing, lying, transitions and gait events, such as turns and missteps, were also explored. A multitude of free-living fall predictors (FLFPs), e.g., the quantity of daily steps, were extracted from activity bouts and events. FLFPs were further categorized into discrete domains (e.g., pace, complexity) defined by conceptual or data-driven models. Heterogeneity was found within the reviewed studies, which includes variance in: terminology (e.g., quantity vs macro), hyperparameters to define/estimate FLFPs, models and domains, and data processing approaches (e.g., the cut-off thresholds to define an ambulatory bout). These inconsistencies led to different results for similar FLFPs, limiting the ability to interpret and compare the evidence.

CONCLUSION

Free-living FRA is a promising avenue for fall prevention. Achieving a harmonized model is necessary to systematically address the inconsistencies in the field and identify FLFPs with the highest predictive values for falls to eventually address intervention programs and fall prevention.

Continuous home monitoring of Parkinson's disease using inertial sensors: A systematic review

Parkinson’s disease (PD) is a progressive neurological disorder of the central nervous system that deteriorates motor functions, while it is also accompanied by a large diversity of non-motor symptoms such as cognitive impairment and mood changes, hallucinations, and sleep disturbance. Parkinsonism is evaluated during clinical examinations and appropriate medical treatments are directed towards alleviating symptoms. Tri-axial accelerometers, gyroscopes, and magnetometers could be adopted to support clinicians in the decision-making process by objectively quantifying the patient’s condition. In this context, at-home data collections aim to capture motor function during daily living and unobstructedly assess the patients’ status and the disease’s symptoms for prolonged time periods. This review aims to collate existing literature on PD monitoring using inertial sensors while it focuses on papers with at least one free-living data capture unsupervised either directly or via videotapes. Twenty-four papers were selected at the end of the process: fourteen investigated gait impairments, eight of which focused on walking, three on turning, two on falls, and one on physical activity; ten articles on the other hand examined symptoms, including bradykinesia, tremor, dyskinesia, and motor state fluctuations in the on/off phenomenon. In summary, inertial sensors are capable of gathering data over a long period of time and have the potential to facilitate the monitoring of people with Parkinson’s, providing relevant information about their motor status. Concerning gait impairments, kinematic parameters (such as duration of gait cycle, step length, and velocity) were typically used to discern PD from healthy subjects, whereas for symptoms’ assessment, researchers were capable of achieving accuracies of over 90% in a free-living environment. Further investigations should be focused on the development of ad-hoc hardware and software capable of providing real-time feedback to clinicians and patients. In addition, features such as the wearability of the system and user comfort, set-up process, and instructions for use, need to be strongly considered in the development of wearable sensors for PD monitoring.