The main objective of this project is to detect fall of Patient using MEMS sensor and monitor Heart Beat in Server
This project proposes an automatic fall detector in a wearable device that can reduce risks by detecting falls and promptly alerting caregivers. For this purpose, we propose cluster-analysis-based user-adaptive fall detection using a fusion of heart rate sensor and accelerometer. The objectives of the proposed fall detector are to have high accuracy with a low-complexity model regardless of diverse conditions. In addition, we verify the performance increment of combining a heart rate sensor with an accelerometer and the effectiveness of the cluster-analysis-based anomaly detection. We also show the effectiveness of the user-adaptive method when using both heart rate and acceleration signals.
In case of any abnormal orientation data values of the user, the system will send an alarm message via GSM to the caretaker. The system design considers a simple and low-cost design with acceptable power consumption rate.
Keywords: Arduino uno, MEMS sensor, GSM, LCD, Buzzer, Power supply
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
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