Literature DB >> 18002880

Home stroke rehabilitation for the upper limbs.

Richard D Willmann1, Gerd Lanfermann, Privender Saini, Annick Timmermans, Jurgen te Vrugt, Stefan Winter.   

Abstract

Philips Research is developing and clinically testing solutions to increase the efficiency and effectiveness of rehabilitation. The Stroke Rehabilitation Exerciser supports patients and therapists in the implementation and execution of a personalized neurological motor exercise plan at home. It enables an efficient therapy planning for the medical professional and increases the training intensity for the patient. The Stroke Rehabilitation Exerciser coaches the patient through a sequence of neurological motor exercises, which are prescribed by the physiotherapist and uploaded to a patient unit. A wireless inertial sensor system records the patient's movements. The data is automatically analyzed for deviations from a personal movement target and patient and therapist are provided with adequate feedback.

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Year:  2007        PMID: 18002880     DOI: 10.1109/IEMBS.2007.4353214

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  10 in total

1.  A Semi-passive Planar Manipulandum for Upper-Extremity Rehabilitation.

Authors:  Chih-Kang Chang; Edward P Washabaugh; Andrew Gwozdziowski; C David Remy; Chandramouli Krishnan
Journal:  Ann Biomed Eng       Date:  2018-04-06       Impact factor: 3.934

Review 2.  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

3.  Technologies and combination therapies for enhancing movement training for people with a disability.

Authors:  David J Reinkensmeyer; Michael L Boninger
Journal:  J Neuroeng Rehabil       Date:  2012-03-30       Impact factor: 4.262

4.  Stroke patients' utilisation of extrinsic feedback from computer-based technology in the home: a multiple case study realistic evaluation.

Authors:  Jack Parker; Susan Mawson; Gail Mountain; Nasrin Nasr; Huiru Zheng
Journal:  BMC Med Inform Decis Mak       Date:  2014-06-05       Impact factor: 2.796

5.  Robotic gaming prototype for upper limb exercise: Effects of age and embodiment on user preferences and movement.

Authors:  Danny Eizicovits; Yael Edan; Iris Tabak; Shelly Levy-Tzedek
Journal:  Restor Neurol Neurosci       Date:  2018       Impact factor: 2.406

6.  A preliminary investigation into the design of pressure cushions and their potential applications for forearm robotic orthoses.

Authors:  N Alavi; S Zampierin; M Komeili; S Cocuzza; S Debei; C Menon
Journal:  Biomed Eng Online       Date:  2017-05-08       Impact factor: 2.819

7.  Quantifying performance on an outdoor agility drill using foot-mounted inertial measurement units.

Authors:  Antonia M Zaferiou; Lauro Ojeda; Stephen M Cain; Rachel V Vitali; Steven P Davidson; Leia Stirling; Noel C Perkins
Journal:  PLoS One       Date:  2017-11-16       Impact factor: 3.240

8.  Wearable systems for shoulder kinematics assessment: a systematic review.

Authors:  Arianna Carnevale; Umile Giuseppe Longo; Emiliano Schena; Carlo Massaroni; Daniela Lo Presti; Alessandra Berton; Vincenzo Candela; Vincenzo Denaro
Journal:  BMC Musculoskelet Disord       Date:  2019-11-15       Impact factor: 2.362

Review 9.  Wearable Health Devices in Health Care: Narrative Systematic Review.

Authors:  Lin Lu; Jiayao Zhang; Yi Xie; Fei Gao; Song Xu; Xinghuo Wu; Zhewei Ye
Journal:  JMIR Mhealth Uhealth       Date:  2020-11-09       Impact factor: 4.773

Review 10.  Technology-assisted training of arm-hand skills in stroke: concepts on reacquisition of motor control and therapist guidelines for rehabilitation technology design.

Authors:  Annick A A Timmermans; Henk A M Seelen; Richard D Willmann; Herman Kingma
Journal:  J Neuroeng Rehabil       Date:  2009-01-20       Impact factor: 4.262

  10 in total

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