Real-World Gait Detection Using a Wrist-Worn Inertial Sensor: Validation Study.

BACKGROUND: Wrist-worn inertial sensors are used in digital health for evaluating mobility in real-world environments. Preceding the estimation of spatiotemporal gait parameters within long-term recordings, gait detection is an important step to identify regions of interest where gait occurs, which requires robust algorithms due to the complexity of arm movements. While algorithms exist for other sensor positions, a comparative validation of algorithms applied to the wrist position on real-world data sets across different disease populations is missing. Furthermore, gait detection performance differences between the wrist and lower back position have not yet been explored but could yield valuable information regarding sensor position choice in clinical studies. OBJECTIVE: The aim of this study was to validate gait sequence (GS) detection algorithms developed for the wrist position against reference data acquired in a real-world context. In addition, this study aimed to compare the performance of algorithms applied to the wrist position to those applied to lower back-worn inertial sensors. METHODS: Participants with Parkinson disease, multiple sclerosis, proximal femoral fracture (hip fracture recovery), chronic obstructive pulmonary disease, and congestive heart failure and healthy older adults (N=83) were monitored for 2.5 hours in the real-world using inertial sensors on the wrist, lower back, and feet including pressure insoles and infrared distance sensors as reference. In total, 10 algorithms for wrist-based gait detection were validated against a multisensor reference system and compared to gait detection performance using lower back-worn inertial sensors. RESULTS: The best-performing GS detection algorithm for the wrist showed a mean (per disease group) sensitivity ranging between 0.55 (SD 0.29) and 0.81 (SD 0.09) and a mean (per disease group) specificity ranging between 0.95 (SD 0.06) and 0.98 (SD 0.02). The mean relative absolute error of estimated walking time ranged between 8.9% (SD 7.1%) and 32.7% (SD 19.2%) per disease group for this algorithm as compared to the reference system. Gait detection performance from the best algorithm applied to the wrist inertial sensors was lower than for the best algorithms applied to the lower back, which yielded mean sensitivity between 0.71 (SD 0.12) and 0.91 (SD 0.04), mean specificity between 0.96 (SD 0.03) and 0.99 (SD 0.01), and a mean relative absolute error of estimated walking time between 6.3% (SD 5.4%) and 23.5% (SD 13%). Performance was lower in disease groups with major gait impairments (eg, patients recovering from hip fracture) and for patients using bilateral walking aids. CONCLUSIONS: Algorithms applied to the wrist position can detect GSs with high performance in real-world environments. Those periods of interest in real-world recordings can facilitate gait parameter extraction and allow the quantification of gait duration distribution in everyday life. Our findings allow taking informed decisions on alternative positions for gait recording in clinical studies and public health. TRIAL REGISTRATION: ISRCTN Registry 12246987; https://www.isrctn.com/ISRCTN12246987. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2021-050785.

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device.

This study aimed to validate a wearable device's walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson's Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and - 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application.Trial registration: ISRCTN - 12246987.

Translating digital healthcare to enhance clinical management: a protocol for an observational study using a digital health technology system to monitor medication adherence and its effect on mobility in people with Parkinson's.

INTRODUCTION: In people with Parkinson's (PwP) impaired mobility is associated with an increased falls risk. To improve mobility, dopaminergic medication is typically prescribed, but complex medication regimens result in suboptimal adherence. Exploring medication adherence and its impact on mobility in PwP will provide essential insights to optimise medication regimens and improve mobility. However, this is typically assessed in controlled environments, during one-off clinical assessments. Digital health technology (DHT) presents a means to overcome this, by continuously and remotely monitoring mobility and medication adherence. This study aims to use a novel DHT system (DHTS) (comprising of a smartphone, smartwatch and inertial measurement unit (IMU)) to assess self-reported medication adherence, and its impact on digital mobility outcomes (DMOs) in PwP. METHODS AND ANALYSIS: This single-centre, UK-based study, will recruit 55 participants with Parkinson's. Participants will complete a range of clinical, and physical assessments. Participants will interact with a DHTS over 7 days, to assess self-reported medication adherence, and monitor mobility and contextual factors in the real world. Participants will complete a motor complications diary (ON-OFF-Dyskinesia) throughout the monitoring period and, at the end, a questionnaire and series of open-text questions to evaluate DHTS usability. Feasibility of the DHTS and the motor complications diary will be assessed. Validated algorithms will quantify DMOs from IMU walking activity. Time series modelling and deep learning techniques will model and predict DMO response to medication and effects of contextual factors. This study will provide essential insights into medication adherence and its effect on real-world mobility in PwP, providing insights to optimise medication regimens. ETHICS AND DISSEMINATION: Ethical approval was granted by London-142 Westminster Research Ethics Committee (REC: 21/PR/0469), protocol V.2.4. Results will be published in peer-reviewed journals. All participants will provide written, informed consent. TRIAL REGISTRATION NUMBER: ISRCTN13156149.

Assessing real-world gait with digital technology? Validation, insights and recommendations from the Mobilise-D consortium.

BACKGROUND: Although digital mobility outcomes (DMOs) can be readily calculated from real-world data collected with wearable devices and ad-hoc algorithms, technical validation is still required. The aim of this paper is to comparatively assess and validate DMOs estimated using real-world gait data from six different cohorts, focusing on gait sequence detection, foot initial contact detection (ICD), cadence (CAD) and stride length (SL) estimates. METHODS: Twenty healthy older adults, 20 people with Parkinson's disease, 20 with multiple sclerosis, 19 with proximal femoral fracture, 17 with chronic obstructive pulmonary disease and 12 with congestive heart failure were monitored for 2.5 h in the real-world, using a single wearable device worn on the lower back. A reference system combining inertial modules with distance sensors and pressure insoles was used for comparison of DMOs from the single wearable device. We assessed and validated three algorithms for gait sequence detection, four for ICD, three for CAD and four for SL by concurrently comparing their performances (e.g., accuracy, specificity, sensitivity, absolute and relative errors). Additionally, the effects of walking bout (WB) speed and duration on algorithm performance were investigated. RESULTS: We identified two cohort-specific top performing algorithms for gait sequence detection and CAD, and a single best for ICD and SL. Best gait sequence detection algorithms showed good performances (sensitivity > 0.73, positive predictive values > 0.75, specificity > 0.95, accuracy > 0.94). ICD and CAD algorithms presented excellent results, with sensitivity > 0.79, positive predictive values > 0.89 and relative errors < 11% for ICD and < 8.5% for CAD. The best identified SL algorithm showed lower performances than other DMOs (absolute error < 0.21 m). Lower performances across all DMOs were found for the cohort with most severe gait impairments (proximal femoral fracture). Algorithms' performances were lower for short walking bouts; slower gait speeds (< 0.5 m/s) resulted in reduced performance of the CAD and SL algorithms. CONCLUSIONS: Overall, the identified algorithms enabled a robust estimation of key DMOs. Our findings showed that the choice of algorithm for estimation of gait sequence detection and CAD should be cohort-specific (e.g., slow walkers and with gait impairments). Short walking bout length and slow walking speed worsened algorithms' performances. Trial registration ISRCTN - 12246987.

Feasibility and usability of a digital health technology system to monitor mobility and assess medication adherence in mild-to-moderate Parkinson's disease.

Introduction: Parkinson's disease (PD) is a neurodegenerative disorder which requires complex medication regimens to mitigate motor symptoms. The use of digital health technology systems (DHTSs) to collect mobility and medication data provides an opportunity to objectively quantify the effect of medication on motor performance during day-to-day activities. This insight could inform clinical decision-making, personalise care, and aid self-management. This study investigates the feasibility and usability of a multi-component DHTS to remotely assess self-reported medication adherence and monitor mobility in people with Parkinson's (PwP). Methods: Thirty participants with PD [Hoehn and Yahr stage I (n = 1) and II (n = 29)] were recruited for this cross-sectional study. Participants were required to wear, and where appropriate, interact with a DHTS (smartwatch, inertial measurement unit, and smartphone) for seven consecutive days to assess medication adherence and monitor digital mobility outcomes and contextual factors. Participants reported their daily motor complications [motor fluctuations and dyskinesias (i.e., involuntary movements)] in a diary. Following the monitoring period, participants completed a questionnaire to gauge the usability of the DHTS. Feasibility was assessed through the percentage of data collected, and usability through analysis of qualitative questionnaire feedback. Results: Adherence to each device exceeded 70% and ranged from 73 to 97%. Overall, the DHTS was well tolerated with 17/30 participants giving a score > 75% [average score for these participants = 89%, from 0 (worst) to 100 (best)] for its usability. Usability of the DHTS was significantly associated with age (ρ = -0.560, BCa 95% CI [-0.791, -0.207]). This study identified means to improve usability of the DHTS by addressing technical and design issues of the smartwatch. Feasibility, usability and acceptability were identified as key themes from PwP qualitative feedback on the DHTS. Conclusion: This study highlighted the feasibility and usability of our integrated DHTS to remotely assess medication adherence and monitor mobility in people with mild-to-moderate Parkinson's disease. Further work is necessary to determine whether this DHTS can be implemented for clinical decision-making to optimise management of PwP.

Design and validation of a multi-task, multi-context protocol for real-world gait simulation.

BACKGROUND: Measuring mobility in daily life entails dealing with confounding factors arising from multiple sources, including pathological characteristics, patient specific walking strategies, environment/context, and purpose of the task. The primary aim of this study is to propose and validate a protocol for simulating real-world gait accounting for all these factors within a single set of observations, while ensuring minimisation of participant burden and safety. METHODS: The protocol included eight motor tasks at varying speed, incline/steps, surface, path shape, cognitive demand, and included postures that may abruptly alter the participants' strategy of walking. It was deployed in a convenience sample of 108 participants recruited from six cohorts that included older healthy adults (HA) and participants with potentially altered mobility due to Parkinson's disease (PD), multiple sclerosis (MS), proximal femoral fracture (PFF), chronic obstructive pulmonary disease (COPD) or congestive heart failure (CHF). A novelty introduced in the protocol was the tiered approach to increase difficulty both within the same task (e.g., by allowing use of aids or armrests) and across tasks. RESULTS: The protocol proved to be safe and feasible (all participants could complete it and no adverse events were recorded) and the addition of the more complex tasks allowed a much greater spread in walking speeds to be achieved compared to standard straight walking trials. Furthermore, it allowed a representation of a variety of daily life relevant mobility aspects and can therefore be used for the validation of monitoring devices used in real life. CONCLUSIONS: The protocol allowed for measuring gait in a variety of pathological conditions suggests that it can also be used to detect changes in gait due to, for example, the onset or progression of a disease, or due to therapy. TRIAL REGISTRATION: ISRCTN-12246987.

Technical validation of real-world monitoring of gait: a multicentric observational study.

INTRODUCTION: Existing mobility endpoints based on functional performance, physical assessments and patient self-reporting are often affected by lack of sensitivity, limiting their utility in clinical practice. Wearable devices including inertial measurement units (IMUs) can overcome these limitations by quantifying digital mobility outcomes (DMOs) both during supervised structured assessments and in real-world conditions. The validity of IMU-based methods in the real-world, however, is still limited in patient populations. Rigorous validation procedures should cover the device metrological verification, the validation of the algorithms for the DMOs computation specifically for the population of interest and in daily life situations, and the users' perspective on the device. METHODS AND ANALYSIS: This protocol was designed to establish the technical validity and patient acceptability of the approach used to quantify digital mobility in the real world by Mobilise-D, a consortium funded by the European Union (EU) as part of the Innovative Medicine Initiative, aiming at fostering regulatory approval and clinical adoption of DMOs.After defining the procedures for the metrological verification of an IMU-based device, the experimental procedures for the validation of algorithms used to calculate the DMOs are presented. These include laboratory and real-world assessment in 120 participants from five groups: healthy older adults; chronic obstructive pulmonary disease, Parkinson's disease, multiple sclerosis, proximal femoral fracture and congestive heart failure. DMOs extracted from the monitoring device will be compared with those from different reference systems, chosen according to the contexts of observation. Questionnaires and interviews will evaluate the users' perspective on the deployed technology and relevance of the mobility assessment. ETHICS AND DISSEMINATION: The study has been granted ethics approval by the centre's committees (London-Bloomsbury Research Ethics committee; Helsinki Committee, Tel Aviv Sourasky Medical Centre; Medical Faculties of The University of Tübingen and of the University of Kiel). Data and algorithms will be made publicly available. TRIAL REGISTRATION NUMBER: ISRCTN (12246987).

The association between age and accelerometry-derived types of habitual daily activity: an observational study over the adult life span in the Netherlands.

BACKGROUND: Advances in sensor technology allow for objective and high-resolution monitoring of physical activity and sedentary behaviour. Novel epidemiological data is required to provide feedback on an individual's habitual daily activity in comparison to peers and might eventually lead to refined physical activity guidelines. METHODS: We merged data of 762 people between 18 and 99 years of age, who all wore a DynaPort MoveMonitor accelerometer on their lower back during 1 week in daily-life, to provide insight into habitual types and durations of daily activities, and examine the association between age and physical activity and sedentary behaviour. RESULTS: We found associations between age and almost all activity outcomes. These associations suggested that physical activity declines and sedentary behaviour increases from the age of 50. We further describe an association with gender, with men walking more often in fewer but longer bouts and having fewer, longer bouts of sitting and standing. CONCLUSIONS: These data provide a valuable reference and may call for more age- and gender-specific activity interventions.

Older Adults with Weaker Muscle Strength Stand up from a Sitting Position with More Dynamic Trunk Use.

The ability to stand up from a sitting position is essential for older adults to live independently. Body-fixed inertial sensors may provide an approach for quantifying the sit-to-stand (STS) in clinical settings. The aim of this study was to determine whether measurements of STS movements using body-fixed sensors yield parameters that are informative regarding changes in STS performance in older adults with reduced muscle strength. In twenty-seven healthy older adults, handgrip strength was assessed as a proxy for overall muscle strength. Subjects were asked to stand up from a chair placed at three heights. Trunk movements were measured using an inertial sensor fixed to the back. Duration, angular range, and maximum angular velocity of STS phases, as well as the vertical velocity of the extension phase, were calculated. Backwards elimination using Generalized Estimating Equations was used to determine if handgrip strength predicted the STS durations and trunk kinematics. Weaker subjects (i.e., with lower handgrip strength) were slower during the STS and showed a larger flexion angular range and a larger extension angular range. In addition, weaker subjects showed a greater maximum angular velocity, which increased with lower seat heights. Measurements with a single inertial sensor did reveal that older adults with lower handgrip strength employed a different strategy to stand up from a sitting position, involving more dynamic use of the trunk. This effect was greatest when elevating body mass. Trunk kinematic parameters were more sensitive to reduced muscle strength than durations.

Instrumented Assessment of Physical Activity Is Associated With Muscle Function but Not With Muscle Mass in a General Population.

OBJECTIVES: Self-reported physical activity has shown to affect muscle-related parameters. As self-report is likely biased, this study aimed to assess the association between instrumented assessment of physical activity (I-PA) and muscle-related parameters in a general population. METHOD: Included were 156 young-to-middle-aged and 80 older community-dwelling adults. Seven days of trunk accelerometry (DynaPort MoveMonitor, McRoberts B.V.) quantified daily physical activity (i.e., active/inactive duration, number and mean duration of active/inactive periods, and number of steps per day). Muscle-related parameters included muscle mass, handgrip strength, and gait speed. RESULTS: I-PA was associated with handgrip strength in young-to-middle-aged adults and with gait speed in older adults. I-PA was not associated with muscle mass in either age group. DISCUSSION: The association between I-PA and muscle-related parameters was age dependent. The lack of an association between I-PA and muscle mass indicates the relevance of muscle function rather than muscle mass.

A novel accelerometry-based algorithm for the detection of step durations over short episodes of gait in healthy elderly.

BACKGROUND: The assessment of short episodes of gait is clinically relevant and easily implemented, especially given limited space and time requirements. BFS (body-fixed-sensors) are small, lightweight and easy to wear sensors, which allow the assessment of gait at relative low cost and with low interference. Thus, the assessment with BFS of short episodes of gait, extracted from dailylife physical activity or measured in a standardised and supervised setting, may add value in the study of gait quality of the elderly. The aim of this study was to evaluate the accuracy of a novel algorithm based on acceleration signals recorded at different human locations (lower back and heels) for the detection of step durations over short episodes of gait in healthy elderly subjects. METHODS: Twenty healthy elderly subjects (73.7 ± 7.9 years old) walked twice a distance of 5 m, wearing a BFS on the lower back, and on the outside of each heel. Moreover, an optoelectronic three-dimensional (3D) motion tracking system was used to detect step durations. A novel algorithm is presented for the detection of step durations from low-back and heel acceleration signals separately. The accuracy of the algorithm was assessed by comparing absolute differences in step duration between the three methods: step detection from the optoelectronic 3D motion tracking system, step detection from the application of the novel algorithm to low-back accelerations, and step detection from the application of the novel algorithm to heel accelerations. RESULTS: The proposed algorithm successfully detected all the steps, without false positives and without false negatives. Absolute average differences in step duration within trials and across subjects were calculated for each comparison, between low-back accelerations and the optoelectronic system were on average 22.4 ± 7.6 ms (4.0 ± 1.3 % of average step duration), between heel accelerations and the optoelectronic system were on average 20.7 ± 11.8 ms (3.7 ± 1.9 %), and between low-back accelerations and heel accelerations were on average 27.8 ± 15.1 ms (4.9 ± 2.5 % of average step duration). CONCLUSIONS: This study showed that the presented novel algorithm detects step durations over short episodes of gait in healthy elderly subjects with acceptable accuracy from low-back and heel accelerations, which provides opportunities to extract a range of gait parameters from short episodes of gait.

Effect of body orientation on proprioception during active and passive motions.

OBJECTIVE: To investigate whether passive and active reproduction of joint position, as well as detection of passive motion (as measures of a subject's proprioception) of the shoulder differ while sitting compared with lying supine. DESIGN: Shoulder proprioception of 28 healthy subjects (age, 22.2 +/- 1.7 yrs, 15 men) was tested. To test proprioception, angular motion (in degrees) for threshold to detection of passive motion and absolute matching error (in degrees) for passive and active reproduction of joint position were measured using an isokinetic dynamometer. As a measure of consistency, the standard deviation per subject and test (threshold to detection of passive motion and passive and active reproduction of joint position) was measured over three trials. The test scores during sitting and lying supine were compared using repeated-measures analysis of variance. RESULTS: No effect of body orientation on threshold to detection of passive motion and passive and active reproduction of joint position scores was found. Significantly larger errors were found during active reproduction of joint position compared with passive reproduction of joint position (F = 58.5; P < 0.01), and subjects were also significantly less accurate during active reproduction of joint position (F = 30.1; P < 0.01). CONCLUSIONS: Body orientation does not significantly influence proprioceptive errors or consistency, whereas movement mode (active or passive) does. The significance of these findings is that, depending on the situation or the patient's ability, proprioception tests can be conducted while they are lying or sitting, but movement modes cannot be used interchangeably.

Relationship among shoulder proprioception, kinematics, and pain after stroke.

OBJECTIVE: To identify a possible relationship among chronic poststroke shoulder pain (PSSP), scapular resting pose, and shoulder proprioception. DESIGN: Case-control study. SETTING: Rehabilitation center. PARTICIPANTS: A total of 21 inpatients with stroke and 10 healthy control subjects. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Orientations of both the contralateral and ipsilateral (ie, paretic and nonparetic) shoulders during rest in degrees, angular displacement (degrees) for threshold to detection of passive motion (TDPM) tests, and absolute error (degrees) for passive reproduction of joint position (PRJP) tests. RESULTS: The contralateral shoulder of patients with PSSP showed more scapular lateral rotation and larger TDPM and PRJP scores than both patients without PSSP and control subjects. Additionally, the contralateral shoulder of patients with deteriorated proprioception showed more scapular lateral rotation than control subjects, whereas their ipsilateral shoulder showed more scapular lateral rotation than both control subjects and patients with good proprioception. CONCLUSIONS: A clear relation among affected shoulder kinematics, affected proprioception, and PSSP was found. In determining the risk of developing PSSP, attention should be paid to a patients shoulder proprioception and kinematics. If both are altered after stroke, this could worsen the initial pathology or cause secondary pathologies and thus initiate a vicious circle of repetitive soft tissue damage leading to chronic PSSP. Additionally, more attention should be paid to the ipsilateral (ie, nonparetic) shoulder because it could be used in determining the risk of developing PSSP in the contralateral (ie, paretic) shoulder.

Kinematics of the contralateral and ipsilateral shoulder: a possible relationship with post-stroke shoulder pain.

OBJECTIVE: Post-stroke shoulder pain is a common phenomenon in hemiplegia and impedes rehabilitation. The aim of this study was to identify a possible relationship between post-stroke shoulder pain, scapula resting position and shoulder motion. METHODS: Shoulder kinematics of 27 patients after stroke (17 men) were compared with 10 healthy age-matched control subjects. Using an electromagnetic tracking device, the kinematics of both the contralateral and ipsilateral (i.e. paretic and non-paretic) arm during active and passive abduction and forward flexion were measured and expressed in Euler angles. RESULTS: Scapular lateral rotation relative to the thorax was increased in patients with post-stroke shoulder pain compared with both patients without post-stroke shoulder pain and control subjects at rest as well as during arm abduction and forward flexion. Additionally, glenohumeral elevation was decreased in patients with post-stroke shoulder pain during passive abduction. No differences were found regarding scapula position (displacement relative to the thorax). CONCLUSION: In patients with post-stroke shoulder pain a particular kinematical shoulder pattern was established, characterized by enhanced scapular lateral rotation and diminished glenohumeral mobility.

Proprioception of the shoulder after stroke.

OBJECTIVE: To investigate position sense and kinesthesia of the shoulders of stroke patients. DESIGN: Case-control study. SETTING: A rehabilitation center. PARTICIPANTS: A total of 22 inpatients with stroke and 10 healthy control subjects. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Angular displacement (in degrees) for threshold to detection of passive motion (TDPM) tests and absolute error (in degrees) for passive reproduction of joint position tests. RESULTS: For patients, the TDPM for internal and external rotation was significantly higher for both the contralateral (paretic) side (internal, 7.92 degrees +/-7.19 degrees ; external, 8.46 degrees +/-8.87 degrees ) and the ipsilateral (nonparetic) side (internal, 4.86 degrees +/-5.03 degrees ; external, 6.09 degrees +/-9.15 degrees ) compared with the control group (internal, 1.83 degrees +/-1.09 degrees ; external, 1.71 degrees +/-.85 degrees ). Also, for internal rotation, TDPM was significantly higher for patients on the contralateral side compared with the ipsilateral side. For passive reproduction of joint position tests, no differences were found. CONCLUSIONS: Both the contralateral and ipsilateral shoulders of stroke patients showed impaired TDPM. Passive reproduction of joint position does not seem to be affected as a result of a stroke. The control of the muscle spindles and central integration or processing problems of the afferent signals provided by muscle spindles might cause these effects.