Parkinson's Disease Detection & Self-Stabilizing Spoon with Health Analysis

The degeneration of nerve cells, which causes Parkinson's disease, a prevalent neurodegenerative ailment that typically affects elderly people, inhibits everyday function, and hinders mobility. Unintentional shivering and hand tremors are early symptoms that make it difficult to do daily tasks like eating. Caretakers find it difficult to supervise patients remotely. Using IoT and sensor network concepts, including ML prediction, our study intends to develop a stabilising spoon and a health monitoring system. The stabilising spoon maintains the bowl's stability by adjusting to the user's shakes or shivers by aligning its head with these forces. With a gyroscope to monitor motion angles and an accelerometer to measure motion speed, we created a prototype device to improve the patient's feeding process. Our project also entails keeping track of the patient's temperature, Spo2 levels, and heart rate while sending the data to a mobile app for status updates. Early on, there were numerous patients, few physicians were available, and significant medical equipment was used in ICUs and other special care units, necessitating the attendance of one nurse or doctor for every patient in various wards. As a result, the patient could not be continually watched, leading to the development of the following issue formulation. The conventional, large-sized medical test equipment. The patient couldn't be located and assisted in time. Extended patient monitoring. Every patient needs human interaction. A lack of readily available medical equipment. It was difficult to continually verify everything. Due to a dearth of specialists and equipment, the majority of patients perished. This study aimed to identify the requirements of medical physicians for wireless patient monitoring. The system uses plug-in analytic components to handle data, and these components may be quickly combined into plans using a graphical programming environment.