ArmSleeve

Ploderer, Bernd; Fong, Justin; Withana, Anusha; Klaic, Marlena; Nair, Siddharth; Crocher, Vincent; Vetere, Frank; Nanayakkara, Suranga

doi:10.1145/2901790.2901799

Cited by 42 publications

(12 citation statements)

References 23 publications

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“…We found that experiential information is essential in co-located stroke rehabilitation for rehabilitation specialists, and that they use a large variety of information other than exercise movement data. However, the focus of home-based therapy systems is on movement data, as they aim at motivating (e.g., Us'em [7]) and monitoring patients (e.g., ArmSleeve [34]). This means that they (1) present movement data to specialists upfront and center, (2) have not enabled capturing experiential information of the movement data, and (3) do not provide means for annotating movement data for context.…”

Section: Discussionmentioning

confidence: 99%

“…Sensor development has been an important step for telerehabilitation and home-based systems to work-we are not denying that. However, consider the following fve recently published systems: a low-cost, wireless home-based rehabilitation sensor that reliably captures upper-limb arm posture and movement [21]; Us'em [7], a wristband-like activity monitor of arm-hand performance designed strictly for patients to motivate the use of an impaired arm during everyday activities; mRes [42], a low-cost device that measures rotational movement, aimed at training dorsal wrist extension and fnger manipulation (both in supination and pronation), with an API for information exchange with telerehabilitation systems; The combination of Microsoft's Kinect 1 sensor data with machine learning to automatically assess stroke rehabilitation exercises [20]; and, ArmSleeve [34], a sensor-embedded sleeve that captures objective upper limb data in patients' daily life, outside rehabilitation exercises, creating a visualization for OTs in a dashboard. In all of these, the initial focus is on the valid collection of data towards motivating correct movement.…”

Section: Sensors and Motivation As The Design Focusmentioning

confidence: 99%

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It’s Not Just the Movement: Experiential Information Needed for Stroke Telerehabilitation

Akinsiku

Avellino

Graham

et al. 2021

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

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Telerehabilitation systems for stroke survivors have been predominantly designed to measure and quantify movement in order to guide and encourage rehabilitation regular exercises at home. We set out to study what aspect of the movement data was essential, to better inform sensor design. We investigated face-to-face stroke rehabilitation sessions through a series of interviews and observations involving 16 stroke rehabilitation specialists including physiatrists, physical therapists, and occupational therapists. We found that specialists are not solely interested in movement data, and that experiential information about stroke survivors' lived experience plays an essential role in specialists interpreting movement data and creating a rehabilitation plan. We argue for a reconceptualization in stroke telerehabilitation that is more inclusive of non-movement data, and present design implications to better account for experiential information in telerehabilitation systems.

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Section: Discussionmentioning

confidence: 99%

Section: Sensors and Motivation As The Design Focusmentioning

confidence: 99%

It’s Not Just the Movement: Experiential Information Needed for Stroke Telerehabilitation

Akinsiku

Avellino

Graham

et al. 2021

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

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“…A wearable sensor prototype has been evaluated in a movement laboratory to establish the feasibility of this approach [20]. The prototype captures motion of the arm through IMUs placed at the wrist, above the elbow, and at the shoulder.…”

Section: Methodsmentioning

confidence: 99%

“…Part of the information displayed on the website was based on sensor data collected in a movement laboratory [20]. We created additional fictional information in consultation with therapists to ensure that the information presented on the dashboard is complete and realistic for a stroke patient.…”

Section: Methodsmentioning

confidence: 99%

How Therapists Use Visualizations of Upper Limb Movement Information From Stroke Patients: A Qualitative Study With Simulated Information

Ploderer¹,

Fong²,

Klaic³

et al. 2016

JMIR Rehabil Assist Technol

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BackgroundStroke is a leading cause of disability worldwide, with upper limb deficits affecting an estimated 30% to 60% of survivors. The effectiveness of upper limb rehabilitation relies on numerous factors, particularly patient compliance to home programs and exercises set by therapists. However, therapists lack objective information about their patients’ adherence to rehabilitation exercises as well as other uses of the affected arm and hand in everyday life outside the clinic. We developed a system that consists of wearable sensor technology to monitor a patient’s arm movement and a Web-based dashboard to visualize this information for therapists.ObjectiveThe aim of our study was to evaluate how therapists use upper limb movement information visualized on a dashboard to support the rehabilitation process.MethodsAn interactive dashboard prototype with simulated movement information was created and evaluated through a user-centered design process with therapists (N=8) at a rehabilitation clinic. Data were collected through observations of therapists interacting with an interactive dashboard prototype, think-aloud data, and interviews. Data were analyzed qualitatively through thematic analysis.ResultsTherapists use visualizations of upper limb information in the following ways: (1) to obtain objective data of patients’ activity levels, exercise, and neglect outside the clinic, (2) to engage patients in the rehabilitation process through education, motivation, and discussion of experiences with activities of daily living, and (3) to engage with other clinicians and researchers based on objective data. A major limitation is the lack of contextual data, which is needed by therapists to discern how movement data visualized on the dashboard relate to activities of daily living.ConclusionsUpper limb information captured through wearable devices provides novel insights for therapists and helps to engage patients and other clinicians in therapy. Consideration needs to be given to the collection and visualization of contextual information to provide meaningful insights into patient engagement in activities of daily living. These findings open the door for further work to develop a fully functioning system and to trial it with patients and clinicians during therapy.

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“…Alankus et al [ 17 ] concentrated on reducing trunk compensatory movement during training in stroke rehabilitation. Ploderer et al [ 18 ]proposed a system named “ArmSleeve”, supporting occupational therapists in stroke rehabilitation, involving exercise and activities addressing the control of compensatory movement. Lorussi et al [ 10 ] integrated a scapular strain sensor that can detect scapula movement with respect to the sternum and rib cage in their wearable textile platform.…”

Section: Technologies For Shoulder Posture Monitoringmentioning

confidence: 99%

Motor Control Training for the Shoulder with Smart Garments

Wang

Baets

Timmermans

et al. 2017

Sensors

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Wearable technologies for posture monitoring and posture correction are emerging as a way to support and enhance physical therapy treatment, e.g., for motor control training in neurological disorders or for treating musculoskeletal disorders, such as shoulder, neck, or lower back pain. Among the various technological options for posture monitoring, wearable systems offer potential advantages regarding mobility, use in different contexts and sustained tracking in daily life. We describe the design of a smart garment named Zishi to monitor compensatory movements and evaluate its applicability for shoulder motor control training in a clinical setting. Five physiotherapists and eight patients with musculoskeletal shoulder pain participated in the study. The attitudes of patients and therapists towards the system were measured using standardized survey instruments. The results indicate that patients and their therapists consider Zishi a credible aid for rehabilitation and patients expect it will help towards their recovery. The system was perceived as highly usable and patients were motivated to train with the system. Future research efforts on the improvement of the customization of feedback location and modality, and on the evaluation of Zishi as support for motor learning in shoulder patients, should be made.

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ArmSleeve

Cited by 42 publications

References 23 publications

It’s Not Just the Movement: Experiential Information Needed for Stroke Telerehabilitation

It’s Not Just the Movement: Experiential Information Needed for Stroke Telerehabilitation

How Therapists Use Visualizations of Upper Limb Movement Information From Stroke Patients: A Qualitative Study With Simulated Information

Motor Control Training for the Shoulder with Smart Garments

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