name: wearable-analysis-agent
description: Analyzes longitudinal wearable sensor data (heart rate, activity, sleep) to detect anomalies and provide personalized health insights.
keywords:
- wearable
- sensor-data
- health-monitoring
- anomaly-detection
- longitudinal-analysis
measurable_outcome: Detects atrial fibrillation and sleep anomalies with >90% accuracy using continuous PPG and accelerometer data.
license: MIT
metadata:
author: Biomedical AI Team
version: "1.0.0"
compatibility:
- system: Python 3.9+
allowed-tools:
- run_shell_command
- read_file
Wearable Analysis Agent
The Wearable Analysis Agent processes data from consumer health devices (Apple Watch, Fitbit, Oura) to monitor vital signs, detect arrhythmias, and analyze lifestyle patterns.
When to Use This Skill
When analyzing raw export data from wearables (XML, JSON, CSV).
To detect irregular heart rhythms (AFib) from PPG data.
For longitudinal sleep quality and circadian rhythm analysis.
To correlate activity levels with biomarkers or symptom logs.
Core Capabilities
Arrhythmia Detection: Algorithms to identify Atrial Fibrillation burdens from irregular tachograms.
Sleep Staging: classifying wake/REM/deep sleep from movement and heart rate variability.
Activity Recognition: Categorizing physical activities and calculating intensity (METs).
Trend Analysis: Detecting significant deviations in resting heart rate or HRV over weeks/months.
Workflow
Ingest: Parse standardized health exports (e.g., Apple Health XML).
1---2name: wearable-analysis-agent3description: <!--4---5<!--6# COPYRIGHT NOTICE7# This file is part of the "Universal Biomedical Skills" project.8# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>9# All Rights Reserved.10#11# This code is proprietary and confidential.12# Unauthorized copying of this file, via any medium is strictly prohibited.13#14# Provenance: Authenticated by MD BABU MIA1516-->1718---19name: wearable-analysis-agent20description: Analyzes longitudinal wearable sensor data (heart rate, activity, sleep) to detect anomalies and provide personalized health insights.21keywords:22 - wearable23 - sensor-data24 - health-monitoring25 - anomaly-detection26 - longitudinal-analysis27measurable_outcome: Detects atrial fibrillation and sleep anomalies with >90% accuracy using continuous PPG and accelerometer data.28license: MIT29metadata:30 author: Biomedical AI Team31 version: "1.0.0"32compatibility:33 - system: Python 3.9+34allowed-tools:35 - run_shell_command36 - read_file37---3839# Wearable Analysis Agent4041The **Wearable Analysis Agent** processes data from consumer health devices (Apple Watch, Fitbit, Oura) to monitor vital signs, detect arrhythmias, and analyze lifestyle patterns.4243## When to Use This Skill4445* When analyzing raw export data from wearables (XML, JSON, CSV).46* To detect irregular heart rhythms (AFib) from PPG data.47* For longitudinal sleep quality and circadian rhythm analysis.48* To correlate activity levels with biomarkers or symptom logs.4950## Core Capabilities51521. **Arrhythmia Detection**: Algorithms to identify Atrial Fibrillation burdens from irregular tachograms.532. **Sleep Staging**: classifying wake/REM/deep sleep from movement and heart rate variability.543. **Activity Recognition**: Categorizing physical activities and calculating intensity (METs).554. **Trend Analysis**: Detecting significant deviations in resting heart rate or HRV over weeks/months.5657## Workflow58591. **Ingest**: Parse standardized health exports (e.g., Apple Health XML).602. **Preprocess**: Clean noise, handle missing data, align timestamps.613. **Analyze**: Apply specific detection algorithms (e.g., `arrhythmia_detector.py`).624. **Report**: Generate summary of anomalies and trends.6364## Example Usage6566**User**: "Analyze my Apple Health export for signs of irregular heart rhythm last month."6768**Agent Action**:69```bash70python3 Skills/Consumer_Health/Wearable_Analysis/arrhythmia_detector.py --input apple_health_export.xml --window "last_month"71```727374<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->
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BioTender-max (@biotender-max) published this skill. Their other Agent Skills are listed on their SkillMD profile.
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