Fall Risk in Relation to Individual Physical Activity Exposure in Patients with Different Neurodegenerative Diseases: a Pilot Study

Differential Effects of Cerebellar Transcranial Direct Current Stimulation with Gait Training on Functional Mobility, Balance, and Ataxia Symptoms

Cerebellar transcranial direct current stimulation (ctDCS) has emerged as a promising, non-invasive, and safe neuromodulatory intervention capable of reducing ataxia symptoms and restoring cerebellum-motor connectivity. However, previous studies have only applied ctDCS in isolation, without association with specific training. This study aimed to assess the effect of ctDCS combined with gait training on functional mobility, balance, and symptoms and severity of ataxia. A randomized, triple-blind, sham-controlled, bi-center clinical trial was conducted with forty-four adults with cerebellar ataxia. Volunteers were randomized to receive five daily sessions of either real ctDCS (n = 11; 2 mA for 25 min) or sham ctDCS (n = 11) during gait training. Functional mobility, balance, and symptoms and severity of ataxia were assessed using the Time Up and Go test, the MiniBESTest, and the Scale for the Assessment and Rating of Ataxia (SARA), respectively, before and after the interventions. Both groups showed improvement in functional mobility, but there was no significant difference between the ctDCS and sham groups. However, the ctDCS group demonstrated significant improvements in cerebellar ataxia severity as reflected by SARA scores, particularly in tests of stance, sitting, speech disturbance, nose-finger test, and heel-shin slide test. Notably, no improvements were observed in balance. This study indicates that while ctDCS combined with gait training may improve specific symptoms of cerebellar ataxia, it does not significantly enhance overall functional mobility compared to sham treatment.

Assessing the clinical utility of inertial sensors for home monitoring in Parkinson's disease: a comprehensive review

This review screened 296 articles on wearable sensors for home monitoring of people with Parkinson's Disease within the PubMed Database, from January 2017 to May 2023. A three-level maturity framework was applied for classifying the aims of 59 studies included: demonstrating technical efficacy, diagnostic sensitivity, or clinical utility. As secondary analysis, user experience (usability and patient adherence) was evaluated. The evidences provided by the studies were categorized and stratified according to the level of maturity. Our results indicate that approximately 75% of articles investigated diagnostic sensitivity, i.e. correlation of sensor-data with clinical parameters. Evidence of clinical utility, defined as improvement on health outcomes or clinical decisions after the use of the wearables, was found only in nine papers. A third of the articles included reported evidence of user experience. Future research should focus more on clinical utility, to facilitate the translation of research results within the management of Parkinson's Disease.

Performance of digital technologies in assessing fall risks among older adults with cognitive impairment: a systematic review

Older adults with cognitive impairment (CI) are twice as likely to fall compared to the general older adult population. Traditional fall risk assessments may not be suitable for older adults with CI due to their reliance on attention and recall. Hence, there is an interest in using objective technology-based fall risk assessment tools to assess falls within this population. This systematic review aims to evaluate the features and performance of technology-based fall risk assessment tools for older adults with CI. A systematic search was conducted across several databases such as PubMed and IEEE Xplore, resulting in the inclusion of 22 studies. Most studies focused on participants with dementia. The technologies included sensors, mobile applications, motion capture, and virtual reality. Fall risk assessments were conducted in the community, laboratory, and institutional settings; with studies incorporating continuous monitoring of older adults in everyday environments. Studies used a combination of technology-based inputs of gait parameters, socio-demographic indicators, and clinical assessments. However, many missed the opportunity to include cognitive performance inputs as predictors to fall risk. The findings of this review support the use of technology-based fall risk assessment tools for older adults with CI. Further advancements incorporating cognitive measures and additional longitudinal studies are needed to improve the effectiveness and clinical applications of these assessment tools. Additional work is also required to compare the performance of existing methods for fall risk assessment, technology-based fall risk assessments, and the combination of these approaches.

Wearable sensors and features for diagnosis of neurodegenerative diseases: A systematic review

Objective

Neurodegenerative diseases affect millions of families around the world, while various wearable sensors and corresponding data analysis can be of great support for clinical diagnosis and health assessment. This systematic review aims to provide a comprehensive overview of the existing research that uses wearable sensors and features for the diagnosis of neurodegenerative diseases.

Methods

A systematic review was conducted of studies published between 2015 and 2022 in major scientific databases such as Web of Science, Google Scholar, PubMed, and Scopes. The obtained studies were analyzed and organized into the process of diagnosis: wearable sensors, feature extraction, and feature selection.

Results

The search led to 171 eligible studies included in this overview. Wearable sensors such as force sensors, inertial sensors, electromyography, electroencephalography, acoustic sensors, optical fiber sensors, and global positioning systems were employed to monitor and diagnose neurodegenerative diseases. Various features including physical features, statistical features, nonlinear features, and features from the network can be extracted from these wearable sensors, and the alteration of features toward neurodegenerative diseases was illustrated. Moreover, different kinds of feature selection methods such as filter, wrapper, and embedded methods help to find the distinctive indicator of the diseases and benefit to a better diagnosis performance.

Conclusions

This systematic review enables a comprehensive understanding of wearable sensors and features for the diagnosis of neurodegenerative diseases.

Multimodal Mobility Assessment Predicts Fall Frequency and Severity in Cerebellar Ataxia

This cohort study aims to evaluate the predictive validity of multimodal clinical assessment and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with cerebellar ataxia (CA).Occurrence, severity, and consequences of falling were prospectively assessed for 6 months in 93 patients with hereditary (N = 36) and sporadic or secondary (N = 57) forms of CA and 63 healthy controls. Participants completed a multimodal clinical and functional fall risk assessment, in-laboratory gait examination, and a 2-week inertial sensor-based daily mobility monitoring. Multivariate logistic regression analyses were performed to evaluate the predictive capacity of all clinical and in- and off-laboratory mobility measures with respect to fall (1) status (non-faller vs. faller), (2) frequency (occasional vs. frequent falls), and (3) severity (benign vs. injurious fall) of patients. 64% of patients experienced one or recurrent falls and 65% of these severe fall-related injuries during prospective assessment. Mobility impairments in patients corresponded to a mild-to-moderate ataxic gait disorder. Patients' fall status and frequency could be reliably predicted (78% and 81% accuracy, respectively), primarily based on their retrospective fall status. Clinical scoring of ataxic symptoms and in- and off-laboratory gait and mobility measures improved classification and provided unique information for the prediction of fall severity (84% accuracy).These results encourage a stepwise approach for fall risk assessment in patients with CA: fall history-taking readily and reliably informs the clinician about patients' general fall risk. Clinical scoring and instrument-based mobility measures provide further in-depth information on the risk of recurrent and injurious falling.

Energy expenditure, body composition and dietary habits in progressive supranuclear palsy

Introduction

Little is known about metabolic changes in progressive supranuclear palsy. Goals of the present study are to: (1) investigate whether early progressive supranuclear palsy is associated with changes in energy expenditure, body composition and dietary intake compared with Parkinson’s disease and healthy controls; (2) assess the accuracy of the Harris–Benedict equation to predict measured rest energy expenditure in progressive supranuclear palsy; (3) verify differences according to sex, phenotypes, disease severity and presence of dysphagia in progressive supranuclear palsy.

Methods

Twenty-one progressive supranuclear palsy, 41 Parkinson’s disease and nine healthy controls were included. Rest energy expenditure was assessed with indirect calorimeter, body composition with bio-impedance analysis and physical activity and dietary intake were estimated with a validated frequency questionnaire. Parametric testing was used to analyze differences between groups.

Results

Progressive supranuclear palsy showed reduced total daily energy expenditure and physical activity compared to both other cohorts (p < 0.001) and a tendency toward lower fat-free mass compared to Parkinson’s disease (p > 0.05). Limited accuracy was shown for the Harris–Benedict equation (accurate prediction frequency < 60%). Greater disease severity was associated with lower rest energy expenditure (p = 0.030), fat-free mass (p = 0.026) and muscle mass (p = 0.029).

Conclusion

Greater disease severity is associated with reduction in rest energy expenditure likely due to the reduction in lean mass and muscle mass. Such data may pave the way to clinical trials evaluating the efficacy of muscle-targeted nutritional support and physical therapy in preserving muscle mass and improving motor performances in progressive supranuclear palsy at early stages.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10846-6.

Walking on common ground: a cross-disciplinary scoping review on the clinical utility of digital mobility outcomes

Physical mobility is essential to health, and patients often rate it as a high-priority clinical outcome. Digital mobility outcomes (DMOs), such as real-world gait speed or step count, show promise as clinical measures in many medical conditions. However, current research is nascent and fragmented by discipline. This scoping review maps existing evidence on the clinical utility of DMOs, identifying commonalities across traditional disciplinary divides. In November 2019, 11 databases were searched for records investigating the validity and responsiveness of 34 DMOs in four diverse medical conditions (Parkinson's disease, multiple sclerosis, chronic obstructive pulmonary disease, hip fracture). Searches yielded 19,672 unique records. After screening, 855 records representing 775 studies were included and charted in systematic maps. Studies frequently investigated gait speed (70.4% of studies), step length (30.7%), cadence (21.4%), and daily step count (20.7%). They studied differences between healthy and pathological gait (36.4%), associations between DMOs and clinical measures (48.8%) or outcomes (4.3%), and responsiveness to interventions (26.8%). Gait speed, step length, cadence, step time and step count exhibited consistent evidence of validity and responsiveness in multiple conditions, although the evidence was inconsistent or lacking for other DMOs. If DMOs are to be adopted as mainstream tools, further work is needed to establish their predictive validity, responsiveness, and ecological validity. Cross-disciplinary efforts to align methodology and validate DMOs may facilitate their adoption into clinical practice.

Effects of multimedia-based fall prevention education on the knowledge, attitudes, or behaviors of patients

OBJECTIVES

Patient safety is regarded as a critical quality monitoring indicator for medical institutions. The effects of a multimedia-based patient education intervention on knowledge, attitudes, and behaviors regarding fall prevention were observed.

METHODS

The study had a quasi-experimental research design and enrolled 140 participants. Seventy participants in the experimental group received multimedia-based patient education and a health education leaflet, while those in the control group received only the health education leaflet. A structured questionnaire was used for data collection at baseline, and a posttest was applied after the intervention.

RESULTS

The participants were predominantly treated in the gastroenterology department (45.7%), followed by the pulmonology department (33.6%). A total of 86.4% of patients had not experienced a fall within 3 months. After the intervention, the average scores for all variables in the experimental group were higher than those in the control group. The results indicate that attitudes, knowledge, and behaviors regarding fall prevention among patients in the pulmonology department were higher than those among patients in the gastroenterology department; the differences were statistically significant.

CONCLUSION

The individualized health education content was of substantial significance for patients with different disease backgrounds and facilitated changes in their knowledge, attitudes, and behaviors regarding falls.

RELEVANCE TO CLINICAL PRACTICE

Multimedia-based patient education influenced inpatients' knowledge, attitudes, and behaviors for preventing falls.

Associations of objectively measured physical activity and sedentary behaviour with fall-related outcomes in older adults: a systematic review

BACKGROUND

Higher physical activity (PA) and lower sedentary behaviour (SB) are associated with better muscle strength, balance, and functional ability, which are imperative for avoiding falls. This systematic review aimed to describe the association between objectively measured PA and SB with falls, fear of falling, and fractures.

METHODS

Six databases were searched from inception to July 21, 2020 for articles reporting the association of objectively measured PA/SB with falls, fear of falling, and/or fractures in community-dwelling older adults ≥60 years old. Results were synthesized in effect-direction heat maps and albatross plots expressed as Pearson's correlation coefficients (R).

RESULTS

A total of 43 articles were included, representing 27,629 (range 26 to 5,545) community-dwelling older adults (mean [SD] age 76.6 [8.4] years, 47% female). Longitudinal associations were reported in 13 articles and cross-sectional associations in 30. Falls were reported in 11 articles, fear of falling in 18 and fractures in 2. Higher PA and lower SB were associated with less fear of falling (median [interquartile range] Rs = steps: -0.214 [0.249; -0.148], total PA: -0.240 [0.267; -0.144], and moderate-to-vigorous PA: -0.180 [0.382; -0.121]), but these associations did not extend to falls or fractures, which showed inconsistent effect directions.

CONCLUSION

Fear of falling is associated with less engagement in PA and more SB, thus indicating that it is a psychological barrier to an active lifestyle. Varying effect directions for associations between PA and SB with falls and fractures may provide evidence for non-linear associations and require further research considering details of the fall or fracture incident.

PROSPERO REGISTRATION NUMBER

CRD42018103910.

Fall prediction in neurological gait disorders: differential contributions from clinical assessment, gait analysis, and daily-life mobility monitoring

Objective

To evaluate the predictive validity of multimodal clinical assessment outcomes and quantitative measures of in- and off-laboratory mobility for fall-risk estimation in patients with different forms of neurological gait disorders.

Methods

The occurrence, severity, and consequences of falls were prospectively assessed for 6 months in 333 patients with early stage gait disorders due to vestibular, cerebellar, hypokinetic, vascular, functional, or other neurological diseases and 63 healthy controls. At inclusion, participants completed a comprehensive multimodal clinical and functional fall-risk assessment, an in-laboratory gait examination, and an inertial-sensor-based daily mobility monitoring for 14 days. Multivariate logistic regression analyses were performed to identify explanatory characteristics for predicting the (1) the fall status (non-faller vs. faller), (2) the fall frequency (occasional vs. frequent falls), and (3) the fall severity (benign vs. injurious fall) of patients.

Results

40% of patients experienced one or frequent falls and 21% severe fall-related injuries during prospective fall assessment. Fall status and frequency could be reliably predicted (accuracy of 78 and 91%, respectively) primarily based on patients' retrospective fall status. Instrumented-based gait and mobility measures further improved prediction and provided independent, unique information for predicting the severity of fall-related consequences.

Interpretation

Falls- and fall-related injuries are a relevant health problem already in early stage neurological gait disorders. Multivariate regression analysis encourages a stepwise approach for fall assessment in these patients: fall history taking readily informs the clinician about patients' general fall risk. In patients at risk of falling, instrument-based measures of gait and mobility provide critical information on the likelihood of severe fall-related injuries.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-021-10504-x.

Falls Risk in Relation to Activity Exposure in High-Risk Older Adults

Background

Physical activity is linked to many positive health outcomes, stimulating the development of exercise programs. However, many falls occur while walking and so promoting activity might paradoxically increase fall rates, causing injuries, and worse quality of life. The relationship between activity exposure and fall rates remains unclear. We investigated the relationship between walking activity (exposure to risk) and fall rates before and after an exercise program (V-TIME).

Methods

One hundred and nine older fallers, 38 fallers with mild cognitive impairment (MCI), and 128 fallers with Parkinson’s disease (PD) were randomly assigned to one of two active interventions: treadmill training only or treadmill training combined with a virtual reality component. Participants were tested before and after the interventions. Free-living walking activity was characterized by volume, pattern, and variability of ambulatory bouts using an accelerometer positioned on the lower back for 1 week. To evaluate that relationship between fall risk and activity, a normalized index was determined expressing fall rates relative to activity exposure (FRA index), with higher scores indicating a higher risk of falls per steps taken.

Results

At baseline, the FRA index was higher for fallers with PD compared to those with MCI and older fallers. Walking activity did not change after the intervention for the groups but the FRA index decreased significantly for all groups (p ≤ .035).

Conclusions

This work showed that V-TIME interventions reduced falls risk without concurrent change in walking activity. We recommend using the FRA index in future fall prevention studies to better understand the nature of intervention programs.

Identification of risk factors for falls in postmenopausal women: a systematic review and meta-analysis

The purpose of this study was to identify risk factors for falls in postmenopausal women and provide evidence for the primary prevention of falls in postmenopausal women. The protocol for this meta-analysis is registered with PROSPERO (CRD42020170927). We searched PubMed, the Cochrane Library and EMBASE for observational studies on the risk factors for falls in postmenopausal women. Review Manager 5.3 was used to calculate the relative risk (RR) or weighted mean difference (WMD) of potential risk factors related to falls. STATA 14.0 was used for the quantitative evaluation of publication bias. Eleven studies with 42,429 patients from 7 countries were included. The main risk factors for falls in postmenopausal women were patient sociodemographic risk factors (age: WMD = 0.37, 95% CI 0.07 to 0.68; body weight: WMD = 0.88, 95% CI 0.56 to 1.12; BMI: WMD = 0.34, 95% CI 0.21 to 0.46; exercise: RR = 0.97, 95% CI 0.94 to 0.99; and FES-I: WMD = 6.60, 95% CI 0.72 to 12.47) and medical risk factors (dietary calcium intake: WMD = - 16.91, 95% CI - 25.80 to - 8.01; previous fracture history: RR = 1.21, 95% CI 1.13 to 1.29; previous falls: RR = 2.02, 95% CI 1.91 to 2.14; number of diseases, ˃ 2: RR = 1.17, 95% CI 1.11 to 1.23; and number of reported chronic health disorders: WMD = 0.30, 95% CI 0.10 to 0.49). Knowledge of the many risk factors associated with falls in postmenopausal women can aid in fall prevention. However, we cannot rule out some additional potential risk factors (age at the onset of menopause, years since last menstruation, hormone therapy and BMD) that need further clinical research.

Real-life gait assessment in degenerative cerebellar ataxia

Objectives

With disease-modifying drugs on the horizon for degenerative ataxias, ecologically valid motor biomarkers are highly warranted. In this observational study, we aimed to unravel and validate markers of ataxic gait in real life by using wearable sensors.

Methods

We assessed gait characteristics of 43 patients with degenerative cerebellar disease (Scale for the Assessment and Rating of Ataxia [SARA] 9.4 ± 3.9) compared with 35 controls by 3 body-worn inertial sensors in 3 conditions: (1) laboratory-based walking; (2) supervised free walking; (3) real-life walking during everyday living (subgroup n = 21). Movement analysis focused on measures of spatiotemporal step variability and movement smoothness.

Results

A set of gait variability measures was identified that allowed us to consistently identify ataxic gait changes in all 3 conditions. Lateral step deviation and a compound measure of spatial step variability categorized patients vs controls with a discrimination accuracy of 0.86 in real life. Both were highly correlated with clinical ataxia severity (effect size ρ = 0.76). These measures allowed detecting group differences even for patients who differed only 1 point in the clinical SARAposture&gait subscore, with highest effect sizes for real-life walking (d = 0.67).

Conclusions

We identified measures of ataxic gait that allowed us not only to capture the gait variability inherent in ataxic gait in real life, but also to demonstrate high sensitivity to small differences in disease severity, with the highest effect sizes in real-life walking. They thus represent promising candidates for motor markers for natural history and treatment trials in ecologically valid contexts.

Classification of evidence

This study provides Class I evidence that a set of gait variability measures, even if accessed in real life, correlated with the clinical severity of ataxia in patients with degenerative cerebellar disease.

Independent domains of daily mobility in patients with neurological gait disorders

The aim of this study was to establish a comprehensive and yet parsimonious model of daily mobility activity in patients with neurological gait disorders. Patients (N = 240) with early-stage neurological (peripheral vestibular, cerebellar, hypokinetic, vascular or functional) gait disorders and healthy controls (N = 35) were clinically assessed with standardized scores related to functional mobility, balance confidence, quality of life, cognitive function, and fall history. Subsequently, daily mobility was recorded for 14 days by means of a body-worn inertial sensor (ActivPAL^®). Fourteen mobility measures derived from ActivPAL recordings were submitted to principle component analysis (PCA). Group differences within each factor obtained from PCA were analyzed and hierarchical regression analysis was performed to identify predictive characteristics from clinical assessment for each factor. PCA yielded five significant orthogonal factors (i.e., mobility domains) accounting for 92.3% of the total variance from inertial-sensor-recordings: ambulatory volume (38.7%), ambulatory pattern (22.3%), postural transitions (13.3%), sedentary volume (10.8%), and sedentary pattern (7.2%). Patients' mobility performance only exhibited reduced scores in the ambulatory volume domain but near-to-normal scores in all remaining domains. Demographic characteristics, clinical scores, and fall history were differentially associated with each domain explaining 19.2–10.2% of their total variance. This study supports a low-dimensional five-domain model for daily mobility behavior in patients with neurological gait disorders that may facilitate monitoring the course of disease or therapeutic intervention effects in ecologically valid and clinically relevant contexts. Further studies are required to explore the determinants that may explain performance differences of patients within each of these domains and to examine the consequences of altered mobility behavior with respect to patients' risk of falling and quality of life.