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NafeesMahmood_MS Thesis_Final.pdf (1.96 MB)

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Enhancing Upper Limb Rehabilitation in Parkinson's Disease with Mixed Reality Combined with Haptic Feedback

Mahmood, Nafees
http://orcid.org/0009-0000-8346-3104
http://rave.ohiolink.edu/etdc/view?acc_num=kent1744803514823073

Abstract Details

2025, MS, Kent State University, College of Arts and Sciences / Department of Computer Science.
This thesis details the design, development, and evaluation of the Virtual Upper Arm Rehabilitation Simulation (VUARS), a portable and programmable simulation system designed to address upper limb motor impairments in individuals with Parkinson's Disease (PD). VUARS integrates a mixed reality headset (Microsoft HoloLens 2) with a haptic device (Geomagic Touch), transitioning a traditional tabletop rehabilitation setup into a mixed reality environment. The system incorporates user-specific customization features, including adjustable button designs, sizes, and layouts, as well as multimodal feedback mechanisms. Precise synchronization between real-world, mixed reality virtual world and haptic device coordinate systems was achieved through a rigorous calibration process upon system development using the Unity 3D game engine. A comprehensive user study was conducted involving both healthy participants (control group) and individuals with PD (target group) to evaluate the system's efficacy. Quantitative and qualitative metrics, such as task completion times, hand motion tracking data, UPDRS scores, Kinesia system data, SUS questionnaire, and NASA-TLX workload assessments, were analyzed. The results demonstrated that the integration of haptic feedback and customization significantly enhanced task performance and user experience. Based on these promising findings, a multi-session learning impact study is currently underway to evaluate the system’s long-term efficacy in mitigating PD-related tremors. This study employs a structured five-day protocol, consisting of three days of training with the system, a rest day, and a retention test on the final day. Future work will focus on extending VUARS for at-home rehabilitation applications, incorporating bimanual interaction capabilities. Additionally, the integration of artificial intelligence and machine learning techniques will enable real-time analysis of time-series and trajectory data, supporting dynamic difficulty adjustments to optimize training outcomes.
Kwangtaek Kim (Advisor)
JungYoon Kim (Committee Member)
Xiang Lian (Committee Member)
90 p.
Computer Science
Parkinson’s disease; Tremors; Haptic feedback and interface; Mixed reality; Resistance training; Upper limb rehabilitation

Recommended Citations

Citations

  • Mahmood, N. (2025). Enhancing Upper Limb Rehabilitation in Parkinson's Disease with Mixed Reality Combined with Haptic Feedback [Master's thesis, Kent State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=kent1744803514823073

    APA Style (7th edition)

  • Mahmood, Nafees. Enhancing Upper Limb Rehabilitation in Parkinson's Disease with Mixed Reality Combined with Haptic Feedback. 2025. Kent State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=kent1744803514823073.

    MLA Style (8th edition)

  • Mahmood, Nafees. "Enhancing Upper Limb Rehabilitation in Parkinson's Disease with Mixed Reality Combined with Haptic Feedback." Master's thesis, Kent State University, 2025. http://rave.ohiolink.edu/etdc/view?acc_num=kent1744803514823073

    Chicago Manual of Style (17th edition)

kent1744803514823073
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© 2025, all rights reserved.
This open access ETD is published by Kent State University and OhioLINK.
Release 3.2.12