Reliability and Validity of Bilateral Ankle Accelerometer Algorithms for Activity Recognition and Walking Speed After Stroke

Dobkin, Bruce H.; Xu, Xiaoyu; Batalin, Maxim; Thomas, Seth; Kaiser, William J.

doi:10.1161/strokeaha.110.611095

Cited by 108 publications

(82 citation statements)

References 32 publications

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“…348,349 Commercially available devices to measure movement when people are outside the rehabilitation clinic are now readily available and becoming more user friendly. These devices include wrist-worn accelerometers, 294,326 ankle-worn accelerometers, 325 step-activity monitors, 328,350 and the more economical alternative, pedometers. 327 Recording movements allow the clinician to measure the quantity and sometimes the types of movements occurring in everyday life.…”

Section: Iia Bmentioning

confidence: 99%

Guidelines for Adult Stroke Rehabilitation and Recovery

Winstein¹,

Stein²,

Arena

et al. 2016

Stroke

2,169

840

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e98Purpose-The aim of this guideline is to provide a synopsis of best clinical practices in the rehabilitative care of adults recovering from stroke. Methods-Writing group members were nominated by the committee chair on the basis of their previous work in relevant topic areas and were approved by the American Heart Association (AHA) Stroke Council's Scientific Statement Oversight Committee and the AHA's Manuscript Oversight Committee. The panel reviewed relevant articles on adults using computerized searches of the medical literature through 2014. The evidence is organized within the context of the AHA framework and is classified according to the joint AHA/American College of Cardiology and supplementary AHA methods of classifying the level of certainty and the class and level of evidence. The document underwent extensive AHA internal and external peer review, Stroke Council Leadership review, and Scientific Statements Oversight Committee review before consideration and approval by the AHA Science Advisory and Coordinating Committee. Results-Stroke rehabilitation requires a sustained and coordinated effort from a large team, including the patient and his or her goals, family and friends, other caregivers (eg, personal care attendants), physicians, nurses, physical and occupational therapists, speech-language pathologists, recreation therapists, psychologists, nutritionists, social workers, and others. Communication and coordination among these team members are paramount in maximizing the effectiveness

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Section: Iia Bmentioning

confidence: 99%

Guidelines for Adult Stroke Rehabilitation and Recovery

Winstein¹,

Stein²,

Arena

et al. 2016

Stroke

2,169

840

View full text Add to dashboard Cite

show abstract

“…The accelerometers were attached via Velcro to adjustable wrist and ankle bands and were worn for the duration of the treatment session. These accelerometers have been tested and used in highly disabled stroke patients in previous research (Dobkin et al, 2011). …”

Section: Methodsmentioning

confidence: 99%

Patient Active Time During Therapy Sessions in Postacute Rehabilitation: Development and Validation of a New Measure

Host¹,

Lang²,

Hildebrand³

et al. 2014

Physical & Occupational Therapy In Geriatrics

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Background and purpose The accurate measurement of therapy intensity in postacute rehabilitation is important for research to improve outcomes in this setting. We developed and validated a measure of Patient Active Time during physical (PT) and occupational therapy (OT) sessions, as a proxy for therapy intensity. Methods This measurement validity study was carried out with 26 older adults admitted to a skilled nursing facility (SNF) for postacute rehabilitation with a variety of main underlying diagnoses, including hip fracture, cardiovascular diseases, stroke, and others. They were participants in a randomized controlled trial that compared an experimental high-intensity therapy to standard-of-care therapy. Patient Active Time was observed by research raters as the total number of minutes that a patient was actively engaging in therapeutic activities during PT and OT sessions. This was compared to patient movement (actigraphy) quantified during some of the same PT/OT sessions using data from three-dimensional accelerometers worn on the patient’s extremities. Results Activity measures were collected for 136 therapy sessions. Patient Active Time had high interrater reliability in both PT (r = 0.995, p < 0.001) and OT (r = 0.95, p = 0.012). Active time was significantly correlated with actigraphy in both PT (r = 0.73, p < 0.001) and OT (r = 0.60, p < 0.001) and discriminated between a high-intensity experimental condition and standard of care rehabilitation: in PT, 47.0 ± 13.5 min versus 16.7 ± 10.1 min (p < 0.001) and in OT, 46.2 ± 15.2 versus 27.7 ± 6.6 min (p < 0.001). Conclusions Systematic observation of Patient Active Time provides an objective, reliable, and valid index of physical activity during PT and OT treatment sessions that has utility as a real-world alternative to the measurement of treatment intensity. This measure could be used to differentiate higher from lower therapy treatment intensity and to help determine the optimal level of active therapy time for patients in postacute and other settings.

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“…A template walk at several speeds for 10 m was used to help train the activity-pattern-recognition algorithm for each subject. 20 The synchronous bilateral raw inertial signals were examined for features related to the timing of components of each stride, including heel-off, toe-off, peak swing, end of swing, and foot flat. A machine learning, Bayesian activity-recognition classifier was developed that grouped activities and set the features that distinguished them.…”

Section: Sensor Platformsmentioning

confidence: 99%

Wearable motion sensors to continuously measure real-world physical activities

Dobkin

2013

Current Opinion in Neurology

Self Cite

135

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Purpose of review Rehabilitation for sensorimotor impairments aims to improve daily activities, walking, exercise, and motor skills. Monitoring of practice and measuring outcomes, however, is usually restricted to laboratory-based procedures and self-reports. Mobile health devices may reverse these confounders of daily care and research trials. Recent findings Wearable, wireless motion sensor data, analyzed by activity pattern-recognition algorithms, can describe the type, quantity, and quality of mobility-related activities in the community. Data transmission from sensors to the cell phone and Internet enable continuous monitoring. Remote access to laboratory-quality data about walking speed, duration and distance, gait asymmetry and smoothness of movements, as well as cycling, exercise, and skills practice, opens new opportunities to engage patients in progressive, personalized therapies with feedback about performance. Clinical trial designs will be able to include remote verification of the integrity of complex physical interventions and compliance with practice, as well as capture repeated, ecologically sound, ratio-scale outcome measures. Summary Given the progressively falling cost of miniaturized wearable gyroscopes, accelerometers, and other physiologic sensors, as well as inexpensive data transmission, sensing systems may become as ubiquitous as cell phones for health care. Neurorehabilitation can develop these mobile health platforms for daily care and clinical trials to improve exercise and fitness, skills learning, and physical functioning.

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Reliability and Validity of Bilateral Ankle Accelerometer Algorithms for Activity Recognition and Walking Speed After Stroke

Cited by 108 publications

References 32 publications

Guidelines for Adult Stroke Rehabilitation and Recovery

Guidelines for Adult Stroke Rehabilitation and Recovery

Patient Active Time During Therapy Sessions in Postacute Rehabilitation: Development and Validation of a New Measure

Wearable motion sensors to continuously measure real-world physical activities

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