Sensing System for Plegic or Paretic Hands Self-Training Motivation
Patients after stroke with paretic or plegic hands require frequent exercises to promote neuroplasticity and to improve hand joint mobilization. Available devices for hand exercising are intended for persons with some level of hand control or provide continuous passive motion with limited patient in...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/6/2414 |
| _version_ | 1827625531025129472 |
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| author | Igor Zubrycki Ewa Prączko-Pawlak Ilona Dominik |
| author_facet | Igor Zubrycki Ewa Prączko-Pawlak Ilona Dominik |
| author_sort | Igor Zubrycki |
| collection | DOAJ |
| description | Patients after stroke with paretic or plegic hands require frequent exercises to promote neuroplasticity and to improve hand joint mobilization. Available devices for hand exercising are intended for persons with some level of hand control or provide continuous passive motion with limited patient involvement. Patients can benefit from self-exercising where they use the other hand to exercise the plegic or paretic one. However, post-stroke neuropsychological complications, apathy, and cognitive impairments such as forgetfulness make regular self-exercising difficult. This paper describes Przypominajka v2—a system intended to support self-exercising, remind about it, and motivate patients. We propose a glove-based device with an on-device machine-learning-based exercise scoring, a tablet-based interface, and a web-based application for therapists. The feasibility of on-device inference and the accuracy of correct exercise classification was evaluated on four healthy participants. Whole system use was described in a case study with a patient with a paretic hand. The anomaly classification has an accuracy of 91.3% and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>f</mi><mn>1</mn></msub></semantics></math></inline-formula> value of 91.6% but achieves poorer results for new users (78% and 81%). The case study showed that patients had a positive reaction to exercising with Przypominajka, but there were issues relating to sensor glove: ease of putting on and clarity of instructions. The paper presents a new way in which sensor systems can support the rehabilitation of after-stroke patients with an on-device machine-learning-based classification that can accurately score and contribute to patient motivation. |
| first_indexed | 2024-03-09T12:38:58Z |
| format | Article |
| id | doaj.art-84c79a3974424548bcefa6a265cfc643 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T12:38:58Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-84c79a3974424548bcefa6a265cfc6432023-11-30T22:21:02ZengMDPI AGSensors1424-82202022-03-01226241410.3390/s22062414Sensing System for Plegic or Paretic Hands Self-Training MotivationIgor Zubrycki0Ewa Prączko-Pawlak1Ilona Dominik2Institute of Automatic Control, Lodz University of Technology, Stefanowskiego 18, 90-537 Lodz, PolandMiejskie Centrum Medyczne im. dr Karola Jonschera, Milionowa 14, 93-113 Lodz, PolandInstitute of Automatic Control, Lodz University of Technology, Stefanowskiego 18, 90-537 Lodz, PolandPatients after stroke with paretic or plegic hands require frequent exercises to promote neuroplasticity and to improve hand joint mobilization. Available devices for hand exercising are intended for persons with some level of hand control or provide continuous passive motion with limited patient involvement. Patients can benefit from self-exercising where they use the other hand to exercise the plegic or paretic one. However, post-stroke neuropsychological complications, apathy, and cognitive impairments such as forgetfulness make regular self-exercising difficult. This paper describes Przypominajka v2—a system intended to support self-exercising, remind about it, and motivate patients. We propose a glove-based device with an on-device machine-learning-based exercise scoring, a tablet-based interface, and a web-based application for therapists. The feasibility of on-device inference and the accuracy of correct exercise classification was evaluated on four healthy participants. Whole system use was described in a case study with a patient with a paretic hand. The anomaly classification has an accuracy of 91.3% and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>f</mi><mn>1</mn></msub></semantics></math></inline-formula> value of 91.6% but achieves poorer results for new users (78% and 81%). The case study showed that patients had a positive reaction to exercising with Przypominajka, but there were issues relating to sensor glove: ease of putting on and clarity of instructions. The paper presents a new way in which sensor systems can support the rehabilitation of after-stroke patients with an on-device machine-learning-based classification that can accurately score and contribute to patient motivation.https://www.mdpi.com/1424-8220/22/6/2414strokestroke rehabilitationparesisplegiawearable devicesensor glove |
| spellingShingle | Igor Zubrycki Ewa Prączko-Pawlak Ilona Dominik Sensing System for Plegic or Paretic Hands Self-Training Motivation Sensors stroke stroke rehabilitation paresis plegia wearable device sensor glove |
| title | Sensing System for Plegic or Paretic Hands Self-Training Motivation |
| title_full | Sensing System for Plegic or Paretic Hands Self-Training Motivation |
| title_fullStr | Sensing System for Plegic or Paretic Hands Self-Training Motivation |
| title_full_unstemmed | Sensing System for Plegic or Paretic Hands Self-Training Motivation |
| title_short | Sensing System for Plegic or Paretic Hands Self-Training Motivation |
| title_sort | sensing system for plegic or paretic hands self training motivation |
| topic | stroke stroke rehabilitation paresis plegia wearable device sensor glove |
| url | https://www.mdpi.com/1424-8220/22/6/2414 |
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