Literature DB >> 30519515

Stroke Patients' Acceptance of a Smart Garment for Supporting Upper Extremity Rehabilitation.

Qi Wang1,2, Annick Timmermans3, Wei Chen4, Jie Jia5,6, Li Ding5, Li Xiong7, Jifeng Rong7, Panos Markopoulos2.   

Abstract

The objective is to evaluate to which extent that Zishi a garment equipped with sensors that can support posture monitoring can be used in upper extremity rehabilitation training of stroke patients. Seventeen stroke survivors (mean age: 55 years old, SD =13.5) were recruited in three hospitals in Shanghai. Patients performed 4 tasks (analytical shoulder flexion, functional shoulder flexion placing a cooking pot, analytical flexion in the scapular plane, and functional flexion in the scapular plane placing a bottle of water) with guided feedback on a tablet that was provided through inertial sensors embedded in the Zishi system at the scapula and the thoracic spine region. After performing the training tasks, patients completed four questionnaires for assessing their motivation, their acceptance of the system, its credibility, and usability. The study participants were highly motivated to train with Zishi and the system was rated high usability, while the subjects had moderate confidence with technology supported training in comparison with the training with therapists. The patients respond positively to using Zishi to support rehabilitation training in a clinical setting. Further developments need to address more on engaging and adaptive feedback. This paper paves the way for larger scale effectiveness studies.

Entities:  

Keywords:  Wearable system; compensatory movement; rehabilitation; smart garment; stroke

Year:  2018        PMID: 30519515      PMCID: PMC6276725          DOI: 10.1109/JTEHM.2018.2853549

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


  26 in total

1.  Forced use of the upper extremity in chronic stroke patients: results from a single-blind randomized clinical trial.

Authors:  J H van der Lee; R C Wagenaar; G J Lankhorst; T W Vogelaar; W L Devillé; L M Bouter
Journal:  Stroke       Date:  1999-11       Impact factor: 7.914

2.  Unmet challenges for rehabilitation after stroke in China.

Authors:  Tetsuya Asakawa; Liang Zong; Liang Wang; Ying Xia; Hiroki Namba
Journal:  Lancet       Date:  2017-07-08       Impact factor: 79.321

3.  Compensatory strategies for reaching in stroke.

Authors:  M C Cirstea; M F Levin
Journal:  Brain       Date:  2000-05       Impact factor: 13.501

4.  Sensor-based arm skill training in chronic stroke patients: results on treatment outcome, patient motivation, and system usability.

Authors:  Annick A A Timmermans; Henk A M Seelen; Richard P J Geers; Privender K Saini; Stefan Winter; Juergen te Vrugt; Herman Kingma
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-04-12       Impact factor: 3.802

5.  EMG and EPP-integrated human-machine interface between the paralyzed and rehabilitation exoskeleton.

Authors:  Yue H Yin; Yuan J Fan; Li D Xu
Journal:  IEEE Trans Inf Technol Biomed       Date:  2012-01-09

6.  Motor compensation and recovery for reaching in stroke patients.

Authors:  A Roby-Brami; A Feydy; M Combeaud; E V Biryukova; B Bussel; M F Levin
Journal:  Acta Neurol Scand       Date:  2003-05       Impact factor: 3.209

7.  Home telehealth reduces healthcare costs.

Authors:  Helen C Noel; Donna C Vogel; Joseph J Erdos; David Cornwall; Forrest Levin
Journal:  Telemed J E Health       Date:  2004       Impact factor: 3.536

8.  Effects of task-oriented robot training on arm function, activity, and quality of life in chronic stroke patients: a randomized controlled trial.

Authors:  Annick A A Timmermans; Ryanne J M Lemmens; Maurice Monfrance; Richard P J Geers; Wilbert Bakx; Rob J E M Smeets; Henk A M Seelen
Journal:  J Neuroeng Rehabil       Date:  2014-03-31       Impact factor: 4.262

9.  TagTrainer: supporting exercise variability and tailoring in technology supported upper limb training.

Authors:  Daniel Tetteroo; Annick A A Timmermans; Henk A M Seelen; Panos Markopoulos
Journal:  J Neuroeng Rehabil       Date:  2014-09-24       Impact factor: 4.262

10.  Motor Control Training for the Shoulder with Smart Garments.

Authors:  Qi Wang; Liesbet De Baets; Annick Timmermans; Wei Chen; Luca Giacolini; Thomas Matheve; Panos Markopoulos
Journal:  Sensors (Basel)       Date:  2017-07-22       Impact factor: 3.576

View more
  3 in total

1.  The State-of-the-Art Sensing Techniques in Human Activity Recognition: A Survey.

Authors:  Sizhen Bian; Mengxi Liu; Bo Zhou; Paul Lukowicz
Journal:  Sensors (Basel)       Date:  2022-06-17       Impact factor: 3.847

Review 2.  Effectiveness of Upper Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: Systematic Review.

Authors:  Jack Parker; Lauren Powell; Susan Mawson
Journal:  J Med Internet Res       Date:  2020-01-08       Impact factor: 5.428

3.  Determining Factors that Influence Adoption of New Post-Stroke Sensorimotor Rehabilitation Devices in the USA.

Authors:  Corey M Morrow; Emily Johnson; Kit N Simpson; Na Jin Seo
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2021-06-30       Impact factor: 4.528

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.