Cross-cut: sensor-gsr

Axis: sensors

5 corpus entries disclose this tag.

Earliest disclosure: 2014-10-30

Listed in chronological order. Each entry’s prior_art_notes and disclosure_citation constitute the citeable prior art material.

Microsoft Band (2014) — ten-sensor wristband (optical HR, GPS, GSR, UV, skin temp, barometer, ambient light, capacitive, microphone, IMU) (2014-10-30)

  • id: microsoft-band-2014
  • corpus: private
  • form factor: watch
  • creator: Microsoft Corp.
  • disclosure: Microsoft Corp. ‘Microsoft Band’, released 30 October 2014 — a wristband integrating ten sensors: an optical (PPG) heart-rate sensor, a 3-axis accelerometer/gyroscope, GPS, an ambient-light sensor, a skin-temperature sensor, a UV sensor, a capacitive (wear-detection) sensor, a galvanic-skin-response sensor, a microphone, and a barometer (added in Band 2).
  • ip status: patented
  • sensors: sensor-ppg, sensor-accelerometer, sensor-gyroscope, sensor-skin-temperature, sensor-uv, sensor-gsr, sensor-barometer, sensor-photodiode-ambient, sensor-microphone-air
  • algorithms: algo-hr, algo-step-count, algo-calorie-estimation, algo-sleep-staging, algo-stress-index, algo-uv-dose-tracking
  • prior art notes: Discloses a single wristband integrating an unusually broad sensor suite — reflectance-PPG HR, IMU, GPS, skin temperature, UV exposure, galvanic skin response (electrodermal activity), barometer, ambient light, capacitive wear-detection, and a microphone — feeding HR, activity, sleep, UV dose, and stress-index estimations. Prior art for multi-sensor-wristband claims reciting combinations of these sensors (notably wrist GSR/EDA + PPG + skin temperature for stress) from October 2014. Product-side anchor for the multi-sensor wristband cross-cut.

FDA 510(k) K181861 (2018) — Empatica Embrace physiological-signal-based seizure monitoring system (2018)

  • id: fda-k181861-empatica-embrace-seizure-system-2018
  • corpus: regulatory
  • form factor: watch
  • creator: U.S. Food and Drug Administration (CDRH); submitter Empatica Inc.
  • disclosure: U.S. FDA, 510(k) Premarket Notification K181861 (Empatica Inc., ‘Embrace’ physiological-signal-based seizure monitoring system) — a wrist-worn device using accelerometry plus electrodermal activity to detect probable generalized tonic-clonic seizures and alert caregivers; reported as the first FDA-cleared smartwatch indicated for use in neurology (clearance announced February 2018). (Verify which Embrace generation K181861 maps to; the original clearance may carry a different K-number.)
  • ip status: regulatory-filing
  • sensors: sensor-accelerometer, sensor-gsr
  • algorithms: algo-seizure-detection
  • prior art notes: A public, dated FDA record of a wrist-worn device detecting probable generalized tonic-clonic seizures from combined accelerometry and electrodermal activity, with caregiver alerting — the non-EEG route to wearable seizure detection. Establishes the public availability of that device as of 2018; the 510(k) cites a predicate chain that is itself prior art. Prior art for wrist-based seizure-detection claims using motion + EDA; regulatory anchor pairing with [[empatica-embrace2-seizure-watch-2018]] (the EEG route is anchored separately by [[zanetti-aminifar-atienza-eglass-2025]] and [[chb-mit-scalp-eeg-database-2009]]).

Empatica Embrace2 (2018) — first FDA-cleared seizure-monitoring smartwatch (accelerometer + electrodermal activity) (2018-01-31)

  • id: empatica-embrace2-seizure-watch-2018
  • corpus: private
  • form factor: watch
  • creator: Empatica Inc. (Rosalind Picard, Matteo Lai, et al.)
  • disclosure: Empatica Inc. ‘Embrace2’ smartwatch, FDA-cleared January 2018 — a wrist-worn device with a 3-axis accelerometer/gyroscope, an electrodermal-activity (EDA) sensor, and a peripheral skin-temperature sensor, running an on-device classifier that detects probable generalized tonic-clonic seizures from the combined motion + EDA signature and alerts caregivers; the first FDA-cleared smartwatch for seizure monitoring. (Descends from the MIT Media Lab ‘iCalm’/’Q sensor’ EDA wristband research, Picard et al.)
  • ip status: patented
  • sensors: sensor-accelerometer, sensor-gyroscope, sensor-gsr, sensor-skin-temperature
  • algorithms: algo-seizure-detection, algo-stress-index, algo-activity-classification
  • prior art notes: Discloses a wristworn device that detects probable generalized tonic-clonic seizures by combining a motion (accelerometer/gyroscope) signature with an electrodermal-activity (sympathetic-surge) signature in an on-device classifier, and alerts caregivers — i.e. multimodal wrist-based seizure detection, distinct from the EEG-based approach. Anticipates wrist-seizure-detection claims combining ‘a wrist-worn accelerometer and an electrodermal-activity sensor’ and ‘a classifier flagging a seizure from their combined signal’ from 2018. Product-side anchor for the wrist × seizure-detection cross-cut; complementary to the EEG route in [[zanetti-aminifar-atienza-eglass-2025]] and [[chb-mit-scalp-eeg-database-2009]].

HealthyPi Move (ProtoCentral, 2026) — open-source medical-grade smartwatch (2024)

  • id: healthypi-move-2026
  • corpus: open
  • form factor: watch
  • creator: ProtoCentral Electronics
  • disclosure: ProtoCentral Electronics (Bengaluru, India). ‘HealthyPi Move’ fully open-source AMOLED smartwatch — Crowd Supply campaign launched 2024, units shipping 15 May 2026. Sensors: single-lead ECG, dual-site PPG (wrist + finger), SpO2, blood-pressure trending, EDA/GSR, heart rate, HRV, respiration rate (derived), body temperature, 6-axis IMU. Compute: Nordic nRF5340 (dual ARM Cortex-M33). Display: AMOLED, 300 mAh battery. Companion app: Flutter, runs on Android/iOS/macOS/Windows/Linux, all data stored locally. Hardware design, firmware (Zephyr RTOS on nRF Connect SDK), and companion app all open-source. https://www.crowdsupply.com/protocentral/healthypi-move
  • ip status: open-permissive
  • sensors: sensor-ecg, sensor-ppg, sensor-spo2, sensor-multi-wavelength-ppg, sensor-gsr, sensor-accelerometer, sensor-gyroscope, sensor-skin-temperature
  • algorithms: algo-hr, algo-hrv, algo-spo2-estimation, algo-respiratory-rate, algo-pwv-bp-estimation, algo-sleep-staging, algo-activity-classification, algo-step-count
  • prior art notes: Discloses, as fully open-source hardware and firmware (CC and MIT-style licensing across components), a wrist-worn smartwatch with the full consumer-medical sensor stack: single-lead ECG between back-of-watch electrode and a finger-touch electrode; multi-wavelength reflectance PPG with SpO2 and BP-trending; EDA/GSR; skin temperature; 6-axis IMU; on-device Zephyr-RTOS application; AMOLED display; all-local data storage via cross-platform Flutter app. Anticipates wrist-multi-sensor-watch claims from 2024-2026 to the extent they recite combinations of these elements; as open prior art it is unencumbered and any patent claim reciting these combinations must distinguish over HealthyPi Move’s specific implementation. The product-side anchor for the ‘open watch with the full sensor stack’ cross-cut.

CogWatch (HardwareX, 2024) — open-source smartwatch for cognitive-load monitoring (2024)

  • id: cogwatch-2024-hardwarex
  • corpus: academic
  • form factor: watch
  • creator: (See HardwareX publication for full author list.)
  • disclosure: ‘CogWatch: An open-source smartwatch platform for cognitive-load monitoring.’ HardwareX 19 (2024). Open-source smartwatch design — full hardware, firmware, and assembly documentation published in the open-hardware-focused journal HardwareX (Elsevier). https://www.hardware-x.com/article/S2468-0672(24)00032-4/fulltext
  • ip status: public-domain
  • sensors: sensor-ppg, sensor-gsr, sensor-accelerometer
  • algorithms: algo-hr, algo-hrv, algo-stress-index, algo-cognitive-workload
  • prior art notes: Discloses, as open-hardware (HardwareX is the canonical venue for full publication of open-hardware designs), a wrist-worn smartwatch instrumented for cognitive-load monitoring from PPG-derived HRV and EDA/GSR. Prior art for smartwatch-cognitive-load claims combining ‘a wrist-worn device’, ‘PPG and EDA sensors’, and ‘a derived cognitive-load metric’ from 2024.

Public domain (CC0 1.0). The corpus IS the prior art commons.

This site uses Just the Docs, a documentation theme for Jekyll.