Literature DB >> 29993937

Modeling and Quantification of Impact of Psychological Factors on Rehabilitation of Stroke Patients.

Zhiqin Qian, Dongyuan Lv, Ying Lv, Zhuming Bi.   

Abstract

The brain damage could lead to the loss of the central nervous system, so a stroke patient may lose the function of dominating his/her body. The rehabilitation aims to maximize the potential to restore a patient who has an impairment. Traditional rehabilitation is to train a patient's muscles and joints under the guidance of doctors to improve the strength of muscles and restore the motor function of joints. However, stroke patients are usually depressed, lonely, and irritable, and they might easily generate negative emotions during a rehabilitation process. With a sole goal of helping patients restore their body functions from the physiology perspective, the traditional rehabilitation took little consideration on the impact of rehabilitation, which is reflected and measured from the perspective of emotions. Therefore, we suggest adding affective regulation to the stroke rehabilitation; in such a way, the patients' exercise could be completed with high intrinsic motivation, and the performance of the rehabilitation process can be enhanced. Two main contributions in the presented works are: 1) the expanded emotional model to represent the status of stroke patients where the impact of psychological factors can be taken into consideration and 2) the quantifiable measurement of rehabilitation performance as well as the corresponding design of experiments to verify the positive impact of psychological adjustment on human subjects. Note that due to the limited conditions, the experimental verification was performed on healthy college students. Since our work focused on modeling and quantification of psychological factors, it is reasonable to expend our work to other human subjects including stoke patients.

Entities:  

Year:  2018        PMID: 29993937     DOI: 10.1109/JBHI.2018.2827100

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  1 in total

1.  Detection of Participation and Training Task Difficulty Applied to the Multi-Sensor Systems of Rehabilitation Robots.

Authors:  Hao Yan; Hongbo Wang; Luige Vladareanu; Musong Lin; Victor Vladareanu; Yungui Li
Journal:  Sensors (Basel)       Date:  2019-10-28       Impact factor: 3.576

  1 in total

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