Literature DB >> 29795772

Enabling Stroke Rehabilitation in Home and Community Settings: A Wearable Sensor-Based Approach for Upper-Limb Motor Training.

Sunghoon I Lee1, Catherine P Adans-Dester2,3, Matteo Grimaldi2, Ariel V Dowling4, Peter C Horak5, Randie M Black-Schaffer2, Paolo Bonato2, Joseph T Gwin4.   

Abstract

High-dosage motor practice can significantly contribute to achieving functional recovery after a stroke. Performing rehabilitation exercises at home and using, or attempting to use, the stroke-affected upper limb during Activities of Daily Living (ADL) are effective ways to achieve high-dosage motor practice in stroke survivors. This paper presents a novel technological approach that enables 1) detecting goal-directed upper limb movements during the performance of ADL, so that timely feedback can be provided to encourage the use of the affected limb, and 2) assessing the quality of motor performance during in-home rehabilitation exercises so that appropriate feedback can be generated to promote high-quality exercise. The results herein presented show that it is possible to detect 1) goal-directed movements during the performance of ADL with a [Formula: see text]-statistic of 87.0% and 2) poorly performed movements in selected rehabilitation exercises with an [Formula: see text]-score of 84.3%, thus enabling the generation of appropriate feedback. In a survey to gather preliminary data concerning the clinical adequacy of the proposed approach, 91.7% of occupational therapists demonstrated willingness to use it in their practice, and 88.2% of stroke survivors indicated that they would use it if recommended by their therapist.

Entities:  

Keywords:  Machine learning; m-health; rehabilitation; remote health monitoring; stroke; wearable sensors; wearable technology

Year:  2018        PMID: 29795772      PMCID: PMC5951609          DOI: 10.1109/JTEHM.2018.2829208

Source DB:  PubMed          Journal:  IEEE J Transl Eng Health Med        ISSN: 2168-2372            Impact factor:   3.316


  44 in total

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Journal:  J Rehabil Res Dev       Date:  1999-07

2.  Estimating Fugl-Meyer clinical scores in stroke survivors using wearable sensors.

Authors:  Silvia Del Din; Shyamal Patel; Claudio Cobelli; Paolo Bonato
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2011

Review 3.  Measuring diagnostic and predictive accuracy in disease management: an introduction to receiver operating characteristic (ROC) analysis.

Authors:  Ariel Linden
Journal:  J Eval Clin Pract       Date:  2006-04       Impact factor: 2.431

Review 4.  Review article: Validity of the KT-1000 knee ligament arthrometer.

Authors:  S Arneja; J Leith
Journal:  J Orthop Surg (Hong Kong)       Date:  2009-04       Impact factor: 1.118

Review 5.  The learned nonuse phenomenon: implications for rehabilitation.

Authors:  E Taub; G Uswatte; V W Mark; D M M Morris
Journal:  Eura Medicophys       Date:  2006-09

6.  Assessment of arm activity using triaxial accelerometry in patients with a stroke.

Authors:  Sanne C van der Pas; Jeanine A Verbunt; Dorien E Breukelaar; Rachma van Woerden; Henk A Seelen
Journal:  Arch Phys Med Rehabil       Date:  2011-09       Impact factor: 3.966

7.  Reliability of the Fugl-Meyer assessment for testing motor performance in patients following stroke.

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Journal:  Phys Ther       Date:  1993-07

8.  Real-world affected upper limb activity in chronic stroke: an examination of potential modifying factors.

Authors:  Ryan R Bailey; Rebecca L Birkenmeier; Catherine E Lang
Journal:  Top Stroke Rehabil       Date:  2015-01-21       Impact factor: 2.177

9.  Exercise preferences are different after stroke.

Authors:  Geraldine Banks; Julie Bernhardt; Leonid Churilov; Toby B Cumming
Journal:  Stroke Res Treat       Date:  2011-07-21

10.  Acceleration metrics are responsive to change in upper extremity function of stroke survivors.

Authors:  M A Urbin; Kimberly J Waddell; Catherine E Lang
Journal:  Arch Phys Med Rehabil       Date:  2014-12-09       Impact factor: 4.060

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  11 in total

1.  Envisioning the use of in-situ arm movement data in stroke rehabilitation: Stroke survivors' and occupational therapists' perspectives.

Authors:  Hee-Tae Jung; Yoojung Kim; Juhyeon Lee; Sunghoon Ivan Lee; Eun Kyoung Choe
Journal:  PLoS One       Date:  2022-10-20       Impact factor: 3.752

2.  Segmentation of shoulder rehabilitation exercises for single and multiple inertial sensor systems.

Authors:  Louise Brennan; Antonio Bevilacqua; Tahar Kechadi; Brian Caulfield
Journal:  J Rehabil Assist Technol Eng       Date:  2020-08-20

Review 3.  A Systematic Review of Wearable Sensors for Monitoring Physical Activity.

Authors:  Annica Kristoffersson; Maria Lindén
Journal:  Sensors (Basel)       Date:  2022-01-12       Impact factor: 3.576

Review 4.  Sensors and Systems for Physical Rehabilitation and Health Monitoring-A Review.

Authors:  Lucas Medeiros Souza do Nascimento; Lucas Vacilotto Bonfati; Melissa La Banca Freitas; José Jair Alves Mendes Junior; Hugo Valadares Siqueira; Sergio Luiz Stevan
Journal:  Sensors (Basel)       Date:  2020-07-22       Impact factor: 3.576

5.  A novel upper-limb function measure derived from finger-worn sensor data collected in a free-living setting.

Authors:  Sunghoon Ivan Lee; Xin Liu; Smita Rajan; Nathan Ramasarma; Eun Kyoung Choe; Paolo Bonato
Journal:  PLoS One       Date:  2019-03-20       Impact factor: 3.240

6.  Thumb and finger movement is reduced after stroke: An observational study.

Authors:  Helleana Eschmann; Martin E Héroux; James H Cheetham; Stephanie Potts; Joanna Diong
Journal:  PLoS One       Date:  2019-06-12       Impact factor: 3.240

Review 7.  Wearable technology in stroke rehabilitation: towards improved diagnosis and treatment of upper-limb motor impairment.

Authors:  Pablo Maceira-Elvira; Traian Popa; Anne-Christine Schmid; Friedhelm C Hummel
Journal:  J Neuroeng Rehabil       Date:  2019-11-19       Impact factor: 4.262

8.  Real-Time Compliant Stream Processing Agents for Physical Rehabilitation.

Authors:  Davide Calvaresi; Jean-Paul Calbimonte
Journal:  Sensors (Basel)       Date:  2020-01-29       Impact factor: 3.576

9.  A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis.

Authors:  Annica Kristoffersson; Maria Lindén
Journal:  Sensors (Basel)       Date:  2020-03-09       Impact factor: 3.576

10.  Development of digital biomarkers for resting tremor and bradykinesia using a wrist-worn wearable device.

Authors:  Nikhil Mahadevan; Charmaine Demanuele; Hao Zhang; Dmitri Volfson; Bryan Ho; Michael Kelley Erb; Shyamal Patel
Journal:  NPJ Digit Med       Date:  2020-01-15
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