Inertia-1: An Open Exploration of Wearable Motion Foundation Models
여성을 위한 사전 스트레스 탐지 + 생리 주기 추적 — Wear OS 생체신호와 Mamba ML 모델 기반.
Deep Learning for Continuous Glucose Monitoring Prediction — Temporal Fusion Transformer, Clarke Error Grid analysis, hypoglycemia prevention for Abbott Libre/Medtronic MiniMed
Adaptive deep learning models for Parkinson’s diagnosis using smartwatch sensor data (PADS Dataset)
Exploratory Data Analysis of wearable health data examining relationships between sleep, stress, lifestyle behaviors, and physiological indicators. Analyzes 55,200 daily records from 300 users over 6 months using Python, Pandas, Matplotlib, and Seaborn.
Proactive Health Insight System using wearable sensor analytics, anomaly detection, Flask, PostgreSQL, and Streamlit
A wearable health monitoring system using ESP32, MAX30102, and MLX90640 to track SpO2, breath rate, and skin temperature — designed for integration in post-surgery shoulder braces. Developed for the eMedha 2021 medical hackathon. For educational use only.
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