增强手部灵活性和认知能力的交互式电子棋盘:工具可用性研究。

IF 2.6 Q2 HEALTH CARE SCIENCES & SERVICES JMIR Human Factors Pub Date : 2024-06-21 DOI:10.2196/56357
Shih-Ying Chien, Alice Mk Wong, Ching-Yi Wu, Sara L Beckman
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引用次数: 0

摘要

背景:脑卒中对健康造成巨大负担,全球每 6 人中就有 1 人受到影响。十分之一的患者会在一年内再次发生中风,而且往往更加严重。令人担忧的是,由于近年来生活方式的改变,越来越多的年轻人受到影响。随着精细运动和认知问题的出现,患者的残疾以及护理人员和医疗资源的压力都在加剧。当代职业疗法通过物体操作和纸笔记录来评估手部灵活性和认知功能。然而,这些评估通常是孤立的,这使得治疗师难以全面评估患者的具体情况。此外,依赖一对一训练和手工记录的评估方法效率低下,而且容易出现转录错误:本研究探讨了在临床环境中使用交互式电子挂板进行中风康复治疗的可行性:方法:共招募了 10 名有中风病史的患者和 10 名健康的老年人。方法:共招募了 10 名脑卒中患者和 10 名健康老年人,两组参与者都在 10 分钟内完成了一系列挑战,包括手动操作、形状识别和颜色辨别。所有参与者都接受了箱块测试和普渡钉板测试,以评估手的灵活性,还接受了一系列认知评估,包括寻迹测试和迷你精神状态检查,作为量化参与者的注意力、执行功能和认知能力的基础:结果:研究结果验证了交互式电子挂板在中风康复临床中的潜在应用。结果:研究结果验证了交互式电子挂板在中风康复临床应用中的潜力:医疗保健专业人员不仅可以将数字电子挂板作为精确的一对一训练工具,还可以将其作为灵活的系统,配置为在线或离线、单人或多人使用。通过数据分析,可以对患者的认知和功能问题进行更有依据的检查。重要的是,患者的记录将在整个练习、练习或测试过程中得到完整保留,通过利用大数据的特点,患者可以获得最准确的康复处方,从而帮助他们获得最佳护理。
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Interactive Electronic Pegboard for Enhancing Manual Dexterity and Cognitive Abilities: Instrument Usability Study.

Background: Strokes pose a substantial health burden, impacting 1 in 6 people globally. One-tenth of patients will endure a second, often more severe, stroke within a year. Alarmingly, a younger demographic is being affected due to recent lifestyle changes. As fine motor and cognitive issues arise, patient disability as well as the strain on caregivers and health care resources is exacerbated. Contemporary occupational therapy assesses manual dexterity and cognitive functions through object manipulation and pen-and-paper recordings. However, these assessments are typically isolated, which makes it challenging for therapists to comprehensively evaluate specific patient conditions. Furthermore, the reliance on one-on-one training and assessment approaches on manual documentation is inefficient and prone to transcription errors.

Objective: This study examines the feasibility of using an interactive electronic pegboard for stroke rehabilitation in clinical settings.

Methods: A total of 10 patients with a history of stroke and 10 healthy older individuals were recruited. With a limit of 10 minutes, both groups of participants underwent a series of challenges involving tasks related to manual operation, shape recognition, and color discrimination. All participants underwent the Box and Block Test and the Purdue Pegboard Test to assess manual dexterity, as well as an array of cognitive assessments, including the Trail Making Test and the Mini-Mental Status Examination, which served as a basis to quantify participants' attention, executive functioning, and cognitive abilities.

Results: The findings validate the potential application of an interactive electronic pegboard for stroke rehabilitation in clinical contexts. Significant statistical differences (P<.01) were observed across all assessed variables, including age, Box and Block Test results, Purdue Pegboard Test outcomes, Trail Making Test-A scores, and Mini-Mental Status Examination performance, between patients with a history of stroke and their healthy older counterparts. Functional and task testing, along with questionnaire interviews, revealed that patients with a history of stroke demonstrated prolonged completion times and slightly inferior performance. Nonetheless, most patients perceived the prototype as user-friendly and engaging. Thus, in the context of patient rehabilitation interventions or the evaluation of patient cognition, physical functioning, or manual dexterity assessments, the developed pegboard could potentially serve as a valuable tool for hand function, attention, and cognitive rehabilitation, thereby mitigating the burden on health care professionals.

Conclusions: Health care professionals can use digital electronic pegboards not only as a precise one-on-one training tool but also as a flexible system that can be configured for online or offline, single-player or multiplayer use. Through data analysis, a more informed examination of patients' cognitive and functional issues can be conducted. Importantly, patient records will be fully retained throughout practices, exercises, or tests, and by leveraging the characteristics of big data, patients can receive the most accurate rehabilitation prescriptions, thereby assisting them in obtaining optimal care.

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来源期刊
JMIR Human Factors
JMIR Human Factors Medicine-Health Informatics
CiteScore
3.40
自引率
3.70%
发文量
123
审稿时长
12 weeks
期刊最新文献
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