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Stream beat-to-beat signals from many Garmin wearables to a single iPad — live.
UeduPAD is a research-grade iOS app developed by the Uedu team. Through Garmin Health SDK, it streams beat-to-beat intervals (BBI) in real time — time-synchronised, with the raw sequence fully preserved — providing a group-level source of physiological data for multimodal learning analytics (MMLA). Stream beat-to-beat signals from many Garmin wearables to a single iPad — live, in class.
Illustrative readout · dummy data
The real open question is how to scale it to an entire class or cohort and align it with classroom events, so that teachers and researchers can obtain multimodal signals they can actually use. UeduPAD was built for this — not yet another individual wellness app, but a classroom-grade physiological signal acquisition device. Individual-level physiological sensing is a solved problem. Scaling it to classrooms, cohorts — and aligning it with what happens in class — is not.
一台 iPad 同時監看多支手錶的逐拍訊號，跨個體同一時間軸比較——群體層級的視角，而非個人健康追蹤。
訊號在課堂當下從手錶經 Garmin Health SDK 直達 iPad，不必等課後才從雲端下載彙整。
每一段生理訊號都與課堂事件日誌時間對齊，支援生理—行為的時序延遲分析。
From wrist to data lake — Watch → SDK → iPad → aligned stream → Uedu platform.
手錶端逐拍偵測心搏間期（RR／BBI）。
透過 BLE 把逐拍訊號即時送到 iPad，非事後雲端匯出。
同時聚合多支手錶，對齊課堂事件時間軸，即時計算 HRV。
寫入 Uedu Fit／Uedu Mind 與 Educational Omics 資料湖供研究分析。
Each cell shows a wearer's live heart rate (BPM) and inter-beat interval (BBI). Device online/offline status and signal fluctuations are shown transparently. One iPad, the whole cohort at a glance. Live BPM & BBI per wearer.
一台 iPad 同時監看多支手錶的逐拍訊號，跨個體共用同一時間軸——群體層級的比較，而非單人追蹤。
逐拍 BBI 不做破壞性壓縮，完整落地，任何 HRV 指標都可在課後重新計算與重製。
生理訊號與課堂事件日誌對齊時間軸，支援生理—行為的時序延遲（temporal lag）分析。
從整班同步比較到個別回溯，隨時在群體視角與個人序列間切換。
RMSSD、pNN50、lnHF、LF／HF 等標準指標以 5 分鐘滑動視窗即時計算。
知情同意流程、去識別化、倫理資料流內建——在 IRB 核准的框架下收集與保存。
Inter-beat intervals and the derived HRV metrics are objective proxies for cardiac autonomic activity. Before algorithmic validation for a specific context, UeduPAD does not treat these signals as direct measures of stress, emotion or learning states; all physiological–behavioural correspondences must be validated by research. Garmin wearable devices are consumer health products and are not for medical use. BBI and HRV metrics are objective proxies for cardiac autonomic activity. Absent context-specific validated algorithms, these signals are not treated as direct measures of stress, emotion, or learning. Garmin devices are consumer wellness products, not medical devices.
大學 Python 等課堂的多模態學習分析示範：讓學生親手體驗生理訊號如何被採集、對齊與解讀。
MMLA 與 PALM（生理感知 AI 輔導）的第一手資料來源，串接 Educational Omics 資料湖供後續分析。
運動科學、認知、學習分析、臨床試驗——同一套採集與同步機制，換場景不換工具。
UeduPAD's data collection is based on an umbrella IRB approved by the Research Ethics Committee (No. 202507EM058). Using the built-in informed consent flow and de-identification SOPs, data collected by researchers in accordance with the rules fall within the scope covered by the IRB. Data collection is covered by an umbrella IRB (No. 202507EM058). Consent flow and de-identification are built into the app's SOPs.
UeduPAD currently operates as a research tool for academic and educational collaboration. If you have ideas for classroom multimodal research or wearable device integration, please get in touch. UeduPAD runs as a research instrument for academic and educational collaboration.