Detection of Tremor Syndrome Among Individuals with Tremor using Eating Aided Spoon for Recovery Monitoring

Abstract

This study presents a system for detecting and monitoring tremor syndromes, aiming to improve the quality of life of people suffering from tremors. The core of this system combines a specially developed tablespoon and smartphone integration to create a comprehensive tool to assess the severity of tremors and provide personalized recommendations. The technical backbone of this solution lies in the integration of an ESP32 microcontroller and an advanced 3-axis gyro sensor that closely measures the angular velocity of hand movements. This data is extremely important for providing a nuanced understanding of the strength of shaking experienced by users. The user experience is further enhanced with the integration of the Blynk mobile application, allowing individuals to seamlessly track average tremor vibrations. This application acts as a channel to send data from the ESP32 microcontroller to the smartphone and allows the user to visualize the tremor intensity using an angular velocity graph. A notable feature of this system is the ability to convert accelerometer values to frequencies, which facilitates the creation of additional angular rate graphs that effectively represent hand tremors. The Blynk app can be a powerful tool for users as it not only allows them to monitor their own tremors, but also gives them insight into the specific type of tremors they may be experiencing. The system takes an important step beyond the data visualization aspect by providing personalized advice based on the type of tremor identified. This proactive approach allows users to take preventive measures and potentially reduce the progression of the disease. The innovative synergy between the table spoon, microcontroller, gyro sensor and smartphone application turn this system into a comprehensive solution that goes beyond simple monitoring. This becomes a dynamic tool for diagnosis, self-management, and intervention.