Wearable Health Monitoring System Embedded In Python
| dc.contributor.author | MEKALA HARSHA VARDHAN SAI 1NH21CS155 SANJAY K 1NH21C5214 PIDAPA SATHISH REDDY 1NH21A1076 POOJARI JATHIN NAIK 1NH21A1077 | |
| dc.date.accessioned | 2025-05-14T07:59:40Z | |
| dc.date.available | 2025-05-14T07:59:40Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | With the growing need for personalized healthcare, the wearable health monitoring devices have emerged as critical tools for continuous health tracking, particularly among elderly, high-risk, and chronic disease patients. This research paper presents a robust and scalable wearable health monitoring system that integrates an Arduino microcontroller with an array of biomedical sensors, designed to capture and analyze various biological parameters in real time. The device combines a heart rate sensor for cardiovascular monitoring, a respiratory sensor to assess breathing patterns, a MEMS sensor to detect body movement and posture, and a temperature sensor to measure core body temperature. These sensors continuously collect data, which is then processed using a machine learning model trained to detect early signs of abnormal health patterns In the event of anomalies such as irregular heart rates, abnormal respiratory rates, sudden movement changes, or elevated temperatures the device automatically generates an SMS alert to designated caregivers or healthcare professionals, enabling timely medical response. The machine learning component enhances accuracy by adapting to individual health baselines, thereby reducing false alarms and improving diagnostic relevance. The wearable's compact, lightweight design allows for prolonged use, promoting user comfort and accessibility. This innovative system addresses the limitations of traditional health monitoring by providing real-time, mobile, and predictive insights, which can pointedly improve patient outcomes. Applications of this device extend beyond individual use to remote patient monitoring, emergency health services, and community health programs, underscoring ts potential for large-scale impact in proactive healthcare management | |
| dc.identifier.uri | http://192.168.75.5:4000/handle/123456789/18907 | |
| dc.language.iso | en | |
| dc.title | Wearable Health Monitoring System Embedded In Python | |
| dc.type | Learning Object |