Published Paper Details:

Parkinson's Disease is a neurodegenerative disorder in the central nervous system that causes significant damage to the nerve cells. Patients with PD experience symptoms such as slow movement, loss of balance, tremors, and stiffness. This paper aimed to develop a new AI device that will be efficient and convenient for PD patients' home monitoring. The assessment of Parkinson's disease is usually difficult because it is a disorder that is characterized by damage of the motor symptoms especially dyskinesia [1]. My AI device is designed to monitor Parkinson's disease by generating a dyskinesia severity score. This device will leverage both AI and LLM AI techniques to collect multimodal data like tremors, movement, and posture. This multimodal data is collected using non-invasive sensors that are installed in the device. The AI algorithms will be significant in this device in analyzing and interpreting the patient-specific patterns from the data collected over some time [1]. It will adapt and refine assessment to ensure there is a comprehensive and personalized pattern of dyskinesia assessment. This device is significant due to its effectiveness in transforming the care management of Parkinson Disease's patients. This device will have the potential to help patients in continuous and unobtrusive home monitoring of Parkinson's Disease which will eventually improve their care and management of the disorder. It will also be significant to the research field in collecting valuable data on the disorder to allow for real-time interventions and improvement of personalized treatment plans. This device is made of cost-effective tools hence it provides a practical solution to PD care and reduces the burden on health facilities.