Instrumented assessment of test battery for physical capability using an accelerometer: a feasibility study

Sensor-Based Quantitative Assessment of Children's Fine Motor Competence: An Instrumented Version of the Placing Bricks Test

The assessment of fine motor competence plays a pivotal role in neuropsychological examinations for the identification of developmental deficits. Several tests have been proposed for the characterization of fine motor competence, with evaluation metrics primarily based on qualitative observation, limiting quantitative assessment to measures such as test durations. The Placing Bricks (PB) test evaluates fine motor competence across the lifespan, relying on the measurement of time to completion. The present study aims at instrumenting the PB test using wearable inertial sensors to complement PB standard assessment with reliable and objective process-oriented measures of performance. Fifty-four primary school children (27 6-year-olds and 27 7-year-olds) performed the PB according to standard protocol with their dominant and non-dominant hands, while wearing two tri-axial inertial sensors, one per wrist. An ad hoc algorithm based on the analysis of forearm angular velocity data was developed to automatically identify task events, and to quantify phases and their variability. The algorithm performance was tested against video recordings in data from five children. Cycle and Placing durations showed a strong agreement between IMU- and Video-derived measurements, with a mean difference <0.1 s, 95% confidence intervals <50% median phase duration, and very high positive correlation (ρ > 0.9). Analyzing the whole population, significant differences were found for age, as follows: six-year-olds exhibited longer cycle durations and higher variability, indicating a stage of development and potential differences in hand dominance; seven-year-olds demonstrated quicker and less variable performance, aligning with the expected maturation and the refined motor control associated with dominant hand training during the first year of school. The proposed sensor-based approach allowed the quantitative assessment of fine motor competence in children, providing a portable and rapid tool for monitoring developmental progress.

Accelerometry applications and methods to assess standing balance in older adults and mobility-limited patient populations: a narrative review

Accelerometers provide an opportunity to expand standing balance assessments outside of the laboratory. The purpose of this narrative review is to show that accelerometers are accurate, objective, and accessible tools for balance assessment. Accelerometry has been validated against current gold standard technology, such as optical motion capture systems and force plates. Many studies have been conducted to show how accelerometers can be useful for clinical examinations. Recent studies have begun to apply classification algorithms to accelerometry balance measures to discriminate populations at risk for falls. In addition to healthy older adults, accelerometry can monitor balance in patient populations such as Parkinson's disease, multiple sclerosis, and traumatic brain injury. The lack of software packages or easy-to-use applications have hindered the shift into the clinical space. Lack of consensus on outcome metrics has also slowed the clinical adoption of accelerometer-based balance assessments. Future studies should focus on metrics that are most helpful to evaluate balance in specific populations and protocols that are clinically efficacious.

Reliability and Accuracy of 2-Minute Step Test in Active and Sedentary Lean Adults

OBJECTIVE

The purpose of this study was to evaluate the intrarater and interrater reliability of the 2-minute step test (2MST) in active and sedentary lean adults and to identify the test cutoff point to differentiate active from sedentary individuals.

METHODS

This observational study involved 4 mixed-sex groups (each with 50 lean participants): group 1, sedentary and aged 18 to 24 years; group 2, active and aged 18 to 24 years; group 3, sedentary and aged 25 to 44 years; and group 4, active and aged 25 to 44 years. The 2MST was administered independently by 2 examiners (with 3 months' training) at 2 different times, with a 7-day interval. Habitual physical activity was evaluated by means of the Baecke Questionnaire (BQ). In statistical analysis, the Pearson correlation coefficient was used to verify the correlation between the 2MST and BQ; intraclass correlation coefficients (ICC_2,3) were used to determine the intrarater and interrater reliability of the 2MST; and the receiver operating characteristic curve was used to identify the accuracy of the 2MST.

RESULTS

Excellent intrarater and interrater reliability were found for all 4 groups (intraclass correlation coefficients ≥ 0.83). Correlating the 2MST score with the BQ score, a significant, positive, weak correlation was observed (r = 0.344, P < .001). For differentiating active from sedentary individuals, the 2MST showed low accuracy (area under the curve = 0.671), with 61% sensitivity and 67% specificity.

CONCLUSION

This study showed that the 2MST is a reliable test with a low amount of inherent error. There was a significant correlation between the 2MST and usual physical activity measured, and slight accuracy in differentiating active from sedentary individuals.

Are Accelerometer-based Functional Outcome Assessments Feasible and Valid After Treatment for Lower Extremity Sarcomas?

BACKGROUND

Aspects of physical functioning, including balance and gait, are affected after surgery for lower limb musculoskeletal tumors. These are not routinely measured but likely are related to how well patients function after resection or amputation for a bone or soft tissue sarcoma. Small, inexpensive portable accelerometers are available that might be clinically useful to assess balance and gait in these patients, but they have not been well studied.

QUESTIONS/PURPOSES

In patients treated for lower extremity musculoskeletal tumors, we asked: (1) Are accelerometer-based body-worn monitor assessments of balance, gait, and timed up-and-go tests (TUG) feasible and acceptable? (2) Do these accelerometer-based body-worn monitor assessments produce clinically useful data (face validity), distinguish between patients and controls (discriminant validity), reflect findings obtained using existing clinical measures (convergent validity) and standard manual techniques in clinic (concurrent validity)?

METHODS

This was a prospective cross-sectional study. Out of 97 patients approached, 34 adult patients treated for tumors in the femur/thigh (19), pelvis/hip (3), tibia/leg (9), or ankle/foot (3) were included in this study. Twenty-seven had limb-sparing surgery and seven underwent amputation. Patients performed standard activities while wearing a body-worn monitor on the lower back, including standing, walking, and TUG tests. Summary measures of balance (area [ellipsis], magnitude [root mean square {RMS}], jerkiness [jerk], frequency of postural sway below which 95% of power of acceleration power spectrum is observed [f95 of postural sway]), gait [temporal outcomes, step length and velocity], and TUG time were derived. Body-worn monitor assessments were evaluated for feasibility by investigating data loss and patient-reported acceptability and comfort. In addition, outcomes in patients were compared with datasets of healthy participants collected in parallel studies using identical methods as in this study to assess discriminant validity. Body-worn monitor assessments were also investigated for their relationships with routine clinical scales (the Musculoskeletal Tumour Society Scoring system [MSTS], the Toronto Extremity Salvage Score [TESS], and the Quality of life-Cancer survivors [QoL-CS)] to assess convergent validity and their agreement with standard manual techniques (video and stopwatch) to assess concurrent validity.

RESULTS

Although this was a small patient group, there were initial indications that body-worn monitor assessments were well-tolerated, feasible to perform, acceptable to patients who responded (95% [19 of 20] of patients found the body-worn monitor acceptable and comfortable and 85% [17 of 20] found it user-friendly), and produced clinically useful data comparable with the evidence. Balance and gait measures distinguished patients and controls (discriminant validity), for instance balance outcome (ellipsis) in patients (0.0475 m/s [95% confidence interval 0.0251 to 0.0810]) was affected compared with controls (0.0007 m/s [95% CI 0.0003 to 0.0502]; p = 0.001). Similarly gait outcome (step time) was affected in patients (0.483 seconds [95% CI 0.451 to 0.512]) compared with controls (0.541 seconds [95% CI 0.496 to 0.573]; p < 0.001). Moreover, body-worn monitor assessments showed relationships with existing clinical scales (convergent validity), for instance ellipsis with MSTS (r = -0.393; p = 0.024). Similarly, manual techniques showed excellent agreement with body-worn monitor assessments (concurrent validity), for instance stopwatch time 22.28 +/- 6.93 seconds with iTUG time 21.18 +/- 6.23 seconds (intraclass correlation coefficient agreement = 0.933; p < 0.001). P < 0.05 was considered statistically significant.

CONCLUSIONS

Although we had a small, heterogeneous patient population, this pilot study suggests that body-worn monitors might be useful clinically to quantify physical functioning in patients treated for lower extremity tumors. Balance and gait relate to disability and quality of life. These measurements could provide clinicians with useful novel information on balance and gait, which in turn could guide rehabilitation strategies.

LEVEL OF EVIDENCE

Level III, diagnostic study.

An Exploratory Factor Analysis of Sensor-Based Physical Capability Assessment

Physical capability (PC) is conventionally evaluated through performance-based clinical assessments. We aimed to transform a battery of sensor-based functional tests into a clinically applicable assessment tool. We used Exploratory Factor Analysis (EFA) to uncover the underlying latent structure within sensor-based measures obtained in a population-based study. Three hundred four community-dwelling older adults (163 females, 80.9 ± 6.4 years), underwent three functional tests (Quiet Stand, QS, 7-meter Walk, 7MW and Chair Stand, CST) wearing a smartphone at the lower back. Instrumented tests provided 73 sensor-based measures, out of which EFA identified a fifteen-factor model. A priori knowledge and the associations with health-related measures supported the functional interpretation and construct validity analysis of the factors, and provided the basis for developing a conceptual model of PC. For example, the “Walking Impairment” domain obtained from the 7MW test was significantly associated with measures of leg muscle power, gait speed, and overall lower extremity function. To the best of our knowledge, this is the first time that a battery of functional tests, instrumented through a smartphone, is used for outlining a sensor-based conceptual model, which could be suitable for assessing PC in older adults and tracking its changes over time.

Remote timed up and go evaluation from activities of daily living reveals changing mobility after surgery

BACKGROUND

Mobility impairment is common in older adults and negatively influences the quality of life. Mobility level may change rapidly following surgery or hospitalization in the elderly. The timed up and go (TUG) is a simple, frequently used clinical test for functional mobility; however, TUG requires supervision from a trained clinician, resulting in infrequent assessments. Additionally, assessment by TUG in clinic settings may not be completely representative of the individual's mobility in their home environment.

OBJECTIVE

In this paper, we introduce a method to estimate TUG from activities detected in free-living, enabling continuous remote mobility monitoring without expert supervision. The method is used to monitor changes in mobility following total hip arthroplasty (THA).

METHODS

Community-living elderly (n  =  239, 65-91 years) performed a standardized TUG in a laboratory and wore a wearable pendant device that recorded accelerometer and barometric sensor data for at least three days. Activities of daily living (ADLs), including walks and sit-to-stand transitions, and their related mobility features were extracted and used to develop a regularized linear model for remote TUG test estimation. Changes in the remote TUG were evaluated in orthopaedic patients (n  =  15, 55-75 years), during 12-weeks period following THA.

MAIN RESULTS

In leave-one-out-cross-validation (LOOCV), a strong correlation (ρ  =  0.70) was observed between the new remote TUG and standardized TUG times. Test-retest reliability of 3-days estimates was high (ICC  =  0.94). Compared to week 2 post-THA, remote TUG was significantly improved at week 6 (11.7  ±  3.9 s versus 8.0  ±  1.8 s, p   <  0.001), with no further change at 12-weeks (8.1  ±  3.9 s, p   =  0.37).

SIGNIFICANCE

Remote TUG can be estimated in older adults using 3-days of ADLs data recorded using a wearable pendant. Remote TUG has discriminatory potential for identifying frail elderly and may provide a convenient way to monitor changes in mobility in unsupervised settings.

From A to Z: Wearable technology explained

Wearable technology (WT) has become a viable means to provide low-cost clinically sensitive data for more informed patient assessment. The benefit of WT seems obvious: small, worn discreetly in any environment, personalised data and possible integration into communication networks, facilitating remote monitoring. Yet, WT remains poorly understood and technology innovation often exceeds pragmatic clinical demand and use. Here, we provide an overview of the common challenges facing WT if it is to transition from novel gadget to an efficient, valid and reliable clinical tool for modern medicine. For simplicity, an A-Z guide is presented, focusing on key terms, aiming to provide a grounded and broad understanding of current WT developments in healthcare.

Prediction of sustained harmonic walking in the free-living environment using raw accelerometry data

OBJECTIVE

Using raw, sub-second-level accelerometry data, we propose and validate a method for identifying and characterizing walking in the free-living environment. We focus on sustained harmonic walking (SHW), which we define as walking for at least 10 s with low variability of step frequency.

APPROACH

We utilize the harmonic nature of SHW and quantify the local periodicity of the tri-axial raw accelerometry data. We also estimate the fundamental frequency of the observed signals and link it to the instantaneous walking (step-to-step) frequency (IWF). Next, we report the total time spent in SHW, number and durations of SHW bouts, time of the day when SHW occurred, and IWF for 49 healthy, elderly individuals.

MAIN RESULTS

The sensitivity of the proposed classification method was found to be 97%, while specificity ranged between 87% and 97% and the prediction accuracy ranged between 94% and 97%. We report the total time in SHW between 140 and 10 min d^-1 distributed between 340 and 50 bouts. We estimate the average IWF to be 1.7 steps-per-second.

SIGNIFICANCE

We propose a simple approach for the detection of SHW and estimation of IWF, based on Fourier decomposition.

Tablet-Based Application for Objective Measurement of Motor Fluctuations in Parkinson Disease

BACKGROUND

The motor subscale of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS-III) has limited applicability for the assessment of motor fluctuations in the home setting.

METHODS

To assess whether a self-administered, tablet-based application can reliably quantify differences in motor performance using two-target finger tapping and forearm pronation-supination tasks in the ON (maximal dopaminergic medication efficacy) and OFF (reemergence of parkinsonian deficits) medication states, we recruited 11 Parkinson disease (PD) patients (age, 60.6 ± 9.0 years; disease duration, 12.8 ± 4.1 years) and 11 healthy age-matched controls (age, 62.5 ± 10.5 years). The total number of taps, tap interval, tap duration, and tap accuracy were algorithmically calculated by the application, using the more affected side in patients and the dominant hand in healthy controls.

RESULTS

Compared to the OFF state, PD patients showed a higher number of taps (84.2 ± 20.3 vs. 54.9 ± 26.9 taps; p = 0.0036) and a shorter tap interval (375.3 ± 97.2 vs. 708.2 ± 412.8 ms; p = 0.0146) but poorer tap accuracy (2,008.4 ± 995.7 vs. 1,111.8 ± 901.3 pixels; p = 0.0055) for the two-target task in the ON state, unaffected by the magnitude of coexistent dyskinesia. Overall, test-retest reliability was high (r >0.75) and the discriminatory ability between OFF and ON states was good (0.60 ≤ AUC ≤ 0.82). The correlations between tapping data and MDS-UPDRS-III scores were only moderate (-0.55 to 0.55).

CONCLUSIONS

A self-administered, tablet-based application can reliably distinguish between OFF and ON states in fluctuating PD patients and may be sensitive to additional motor phenomena, such as accuracy, not captured by the MDS-UPDRS-III.

Objective assessment of movement competence in children using wearable sensors: An instrumented version of the TGMD-2 locomotor subtest

Movement competence (MC) is defined as the development of sufficient skill to assure successful performance in different physical activities. Monitoring children MC during maturation is fundamental to detect early minor delays and define effective intervention. To this purpose, several MC assessment batteries are available. When evaluating movement strategies, with the aim of identifying specific skill components that may need improving, widespread MC assessment is limited by high time consumption for scoring and the need for trained operators to ensure reliability. This work aims to facilitate and support the assessment by designing, implementing and validating an instrumented version of the TGMD-2 locomotor subtest based on Inertial Measurement Units (IMUs) to quantify MC in children rapidly and objectively. 45 typically developing children, aged 6-10, performed the TGMD-2 locomotor subtest (six skills). During the tests, children wore five IMUs mounted on lower back, on ankles and on wrists. Sensor and video recordings of the tests were collected. Three expert evaluators performed the standard assessment of TGMD-2. Using theoretical and modelling approaches, algorithms were implemented to automatically score children tests based on IMUs' data. The automatic assessment, compared to the standard one, showed an agreement higher than 87% on average on the entire group for each skill and a reduction of time for scoring from 15 to 2min per participant. Results support the use of IMUs for MC assessment: this approach will allow improving the usability of MC assessment, supporting objectively evaluator decisions and reducing time requirement for the evaluation of large groups.

A multi-resolution investigation for postural transition detection and quantification using a single wearable

BACKGROUND

Multi-resolution analyses involving wavelets are commonly applied to data derived from accelerometer-based wearable technologies (wearables) to identify and quantify postural transitions (PTs). Previous studies fail to provide rationale to inform their choice of wavelet and scale approximation when utilising discrete wavelet transforms. This study examines varying combinations of those parameters to identify best practice recommendations for detecting and quantifying sit-to-stand (SiSt) and stand-to-sit (StSi) PTs.

METHODS

39 young and 37 older participants completed three SiSt and StSi PTs on supported and unsupported chair types while wearing a single tri-axial accelerometer-based wearable on the lower back. Transition detection and duration were calculated through peak detection within the signal vector magnitude for a range of wavelets and scale approximations. A laboratory reference measure (2D video) was used for comparative analysis.

RESULTS

Detection accuracy of wavelet and scale combinations for the transitions was excellent for both SiSt (87-97%) and StSi (82-86%) PT-types. The duration of PTs derived from the wearable showed considerable bias and poor agreement compared with the reference videos. No differences were observed between chair types and age groups respectively.

CONCLUSIONS

Improved detection of PTs could be achieved through the incorporation of different wavelet and scale combinations for the assessment of specific PT types in clinical and free-living settings. An upper threshold of 5th scale approximations is advocated for improved detection of multiple PT-types. However, care should be taken estimating the duration of PTs using wearables.

Pilot Randomised Controlled Trial of a Web-Based Intervention to Promote Healthy Eating, Physical Activity and Meaningful Social Connections Compared with Usual Care Control in People of Retirement Age Recruited from Workplaces

BACKGROUND

Lifestyle interventions delivered during the retirement transition might promote healthier ageing. We report a pilot randomised controlled trial (RCT) of a web-based platform (Living, Eating, Activity and Planning through retirement; LEAP) promoting healthy eating (based on a Mediterranean diet (MD)), physical activity (PA) and meaningful social roles.

METHODS

A single blinded, two-arm RCT with individual allocation. Seventy-five adult regular internet users living in Northeast England, within two years of retirement, were recruited via employers and randomised in a 2:1 ratio to receive LEAP or a 'usual care' control. Intervention arm participants were provided with a pedometer to encourage self-monitoring of PA goals. Feasibility of the trial design and procedures was established by estimating recruitment and retention rates, and of LEAP from usage data. At baseline and 8-week follow-up, adherence to a MD derived from three 24-hour dietary recalls and seven-day PA by accelerometry were assessed. Healthy ageing outcomes (including measures of physiological function, physical capability, cognition, psychological and social wellbeing) were assessed and acceptability established by compliance with measurement protocols and completion rates. Thematically analysed, semi-structured, qualitative interviews assessed acceptability of the intervention, trial design, procedures and outcome measures.

RESULTS

Seventy participants completed the trial; 48 (96%) participants in the intervention and 22 (88%) in the control arm. Participants had considerable scope for improvement in diet as assessed by MD score. LEAP was visited a median of 11 times (range 1-80) for a mean total time of 2.5 hours (range 5.5 min- 8.3 hours). 'Moving more', 'eating well' and 'being social' were the most visited modules. At interview, participants reported that diet and PA modules were important and acceptable within the context of healthy ageing. Participants found both trial procedures and outcome assessments acceptable.

CONCLUSIONS

The trial procedures and the LEAP intervention proved feasible and acceptable. Effectiveness and cost-effectiveness of LEAP to promote healthy lifestyles warrant evaluation in a definitive RCT.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02136381.

Multivariate Analyses and Classification of Inertial Sensor Data to Identify Aging Effects on the Timed-Up-and-Go Test

Many tests can crudely quantify age-related mobility decrease but instrumented versions of mobility tests could increase their specificity and sensitivity. The Timed-up-and-Go (TUG) test includes several elements that people use in daily life. The test has different transition phases: rise from a chair, walk, 180° turn, walk back, turn, and sit-down on a chair. For this reason the TUG is an often used test to evaluate in a standardized way possible decline in balance and walking ability due to age and or pathology. Using inertial sensors, qualitative information about the performance of the sub-phases can provide more specific information about a decline in balance and walking ability. The first aim of our study was to identify variables extracted from the instrumented timed-up-and-go (iTUG) that most effectively distinguished performance differences across age (age 18-75). Second, we determined the discriminative ability of those identified variables to classify a younger (age 18-45) and older age group (age 46-75). From healthy adults (n = 59), trunk accelerations and angular velocities were recorded during iTUG performance. iTUG phases were detected with wavelet-analysis. Using a Partial Least Square (PLS) model, from the 72-iTUG variables calculated across phases, those that explained most of the covariance between variables and age were extracted. Subsequently, a PLS-discriminant analysis (DA) assessed classification power of the identified iTUG variables to discriminate the age groups. 27 variables, related to turning, walking and the stand-to-sit movement explained 71% of the variation in age. The PLS-DA with these 27 variables showed a sensitivity and specificity of 90% and 85%. Based on this model, the iTUG can accurately distinguish young and older adults. Such data can serve as a reference for pathological aging with respect to a widely used mobility test. Mobility tests like the TUG supplemented with smart technology could be used in clinical practice.

A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson's disease

Background

There is growing interest in having objective assessment of health-related outcomes using technology-based devices that provide unbiased measurements which can be used in clinical practice and scientific research. Many studies have investigated the clinical manifestations of Parkinson’s disease using such devices. However, clinimetric properties and clinical validation vary among the different devices.

Methods

Given such heterogeneity, we sought to perform a systematic review in order to (i) list, (ii) compare and (iii) classify technological-based devices used to measure motor function in individuals with Parkinson's disease into three groups, namely wearable, non-wearable and hybrid devices. A systematic literature search of the PubMed database resulted in the inclusion of 168 studies. These studies were grouped based on the type of device used. For each device we reviewed availability, use, reliability, validity, and sensitivity to change. The devices were then classified as (i) ‘recommended’, (ii) ‘suggested’ or (iii) ‘listed’ based on the following criteria: (1) used in the assessment of Parkinson’s disease (yes/no), (2) used in published studies by people other than the developers (yes/no), and (3) successful clinimetric testing (yes/no).

Results

Seventy-three devices were identified, 22 were wearable, 38 were non-wearable, and 13 were hybrid devices. In accordance with our classification method, 9 devices were ‘recommended’, 34 devices were ‘suggested’, and 30 devices were classified as ‘listed’. Within the wearable devices group, the Mobility Lab sensors from Ambulatory Parkinson’s Disease Monitoring (APDM), Physilog®, StepWatch 3, TriTrac RT3 Triaxial accelerometer, McRoberts DynaPort, and Axivity (AX3) were classified as ‘recommended’. Within the non-wearable devices group, the Nintendo Wii Balance Board and GAITRite® gait analysis system were classified as ‘recommended’. Within the hybrid devices group only the Kinesia® system was classified as ‘recommended’.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-016-0136-7) contains supplementary material, which is available to authorized users.

iCap: Instrumented assessment of physical capability

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Instrumented testing of five physical capability tasks with a single accelerometer.

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Evaluated on a large cohort of older adults.

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iCap provides robust quantitative data about physical capability.

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iCap captures gait and postural control data known as sensitive to ageing/pathology.

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Methodology may have practical utility in a wide range of surveys and studies.

Objectives

The aims of this study were to (i) investigate instrumented physical capability (iCap) as a valid method during a large study and (ii) determine whether iCap can provide important additional features of postural control and gait to categorise cohorts not previously possible with manual recordings.

Study design

Cross-sectional analysis involving instrumented testing on 74 adults who were recruited as part of a pilot intervention study; LiveWell. Participants wore a single accelerometer-based monitor (lower back) during standardised physical capability tests so that outcomes could be compared directly with manual recordings (stopwatch and measurement tape) made concurrently.

Main outcome measures

Time, distance, postural control and gait characteristics.

Results

Agreement between manual and iCap ranged from moderate to excellent (0.649–0.983) with mean differences between methods low and deemed acceptable. Additionally, iCap successfully quantified (i) postural control characteristics which showed sensitivity to distinguish between 5 variations of the standing balance test and (ii) 14 gait characteristics known to be sensitive to age/pathology.

Conclusions

Our findings show that iCap can provide robust quantitative data about physical capability during standardised tests while also providing sensitive (age/pathology) postural control and gait characteristics not previously quantifiable with manual recordings. The methodology which we propose may have practical utility in a wide range of clinical and public health surveys and studies, including intervention studies, where assessment could be undertaken within diverse settings. This will need to be tested in further validation studies in a wider range of settings.

Validation of an Accelerometer to Quantify a Comprehensive Battery of Gait Characteristics in Healthy Older Adults and Parkinson's Disease: Toward Clinical and at Home Use

Measurement of gait is becoming important as a tool to identify disease and disease progression, yet to date its application is limited largely to specialist centers. Wearable devices enables gait to be measured in naturalistic environments, however questions remain regarding validity. Previous research suggests that when compared with a laboratory reference, measurement accuracy is acceptable for mean but not variability or asymmetry gait characteristics. Some fundamental reasons for this have been presented, (e.g., synchronization, different sampling frequencies) but to date this has not been systematically examined. The aims of this study were to: 1) quantify a comprehensive range of gait characteristics measured using a single triaxial accelerometer-based monitor; 2) examine outcomes and monitor performance in measuring gait in older adults and those with Parkinson's disease (PD); and 3) carry out a detailed comparison with those derived from an instrumented walkway to account for any discrepancies. Fourteen gait characteristics were quantified in 30 people with incident PD and 30 healthy age-matched controls. Of the 14 gait characteristics compared, agreement between instruments was excellent for four (ICCs 0.913-0.983); moderate for four (ICCs 0.508-0.766); and poor for six characteristics (ICCs 0.637-0.370). Further analysis revealed that differences reflect an increased sensitivity of accelerometry to detect motion, rather than measurement error. This is most likely because accelerometry measures gait as a continuous activity rather than discrete footfall events, per instrumented tools. The increased sensitivity shown for these characteristics will be of particular interest to researchers keen to interpret "real-world" gait data. In conclusion, use of a body-worn monitor is recommended for the measurement of gait but is likely to yield more sensitive data for asymmetry and variability features.