Exploring the Impact of an Interactive Electronic Pegboard on Manual Dexterity and Cognitive Skills of Stroke Patients: A Preliminary Analysis (Preprint)

Background As individuals age, the incidence and mortality rates of cerebrovascular accidents significantly rise, leading to fine motor impairments and cognitive deficits that impact daily life. In modern occupational therapy, assessing manual dexterity and cognitive functions typically involves observation of patients interacting with physical objects. However, this pen-and-paper method is not only time-consuming, relying heavily on therapist involvement, but also often inaccurate. Digital assessment methods, therefore, have the potential to increase the accuracy of diagnosis, as well as decrease the workload of health care professionals. Objective This study examined the feasibility of an interactive electronic pegboard for the assessment and rehabilitation of patients with stroke. Methods We explored the pegboard’s clinical applicability by examining the relationship among stages, timing, and difficulty settings, as well as their alignment with patient capabilities. In total, 10 participants used a prototype of the pegboard for functional and task assessments; questionnaire interviews were conducted simultaneously to collect user feedback. Results Patients with stroke consistently required more time to complete tasks than expected, significantly deviating from the initial time frames. Additionally, the participants exhibited a slight reduction in performance levels in both manual dexterity and cognitive abilities. Insights from questionnaire responses revealed that the majority of participants found the prototype interface easy and enjoyable to use, with good functionality. Conclusions This preliminary investigation supports the efficacy of interactive electronic pegboards for the rehabilitation of the hand functions of patients with stroke, as well as training their attentional and cognitive abilities. This digital technology could potentially alleviate the burden of health care workers, positioning it as a valuable and intelligent precision health care tool.