This paper is in the following e-collection/theme issue:

Design and Usability of Consumer Health Tech and Home Monitoring Devices (228) Wearable Devices and Sensors (903) Digital Biomarkers and Digital Phenotyping (198) Machine Learning (1501) Artificial Intelligence (1421)

Published on in Vol 10 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42714, first published .
Detecting Medication-Taking Gestures Using Machine Learning and Accelerometer Data Collected via Smartwatch Technology: Instrument Validation Study

Detecting Medication-Taking Gestures Using Machine Learning and Accelerometer Data Collected via Smartwatch Technology: Instrument Validation Study

Detecting Medication-Taking Gestures Using Machine Learning and Accelerometer Data Collected via Smartwatch Technology: Instrument Validation Study

Authors of this article:

Chrisogonas Odero Odhiambo1 Author Orcid Image ;   Lukacs Ablonczy2 Author Orcid Image ;   Pamela J Wright3 Author Orcid Image ;   Cynthia F Corbett3 Author Orcid Image ;   Sydney Reichardt2 Author Orcid Image ;   Homayoun Valafar1 Author Orcid Image
Article Authors Cited by (2) Tweetations (4) Metrics

Journals

  1. Smith A, Azeem M, Odhiambo C, Wright P, Diktas H, Upton S, Martin C, Froeliger B, Corbett C, Valafar H. Toward Concurrent Identification of Human Activities with a Single Unifying Neural Network Classification: First Step. Sensors 2024;24(14):4542 View
  2. Amirthalingam P, Alatawi Y, Chellamani N, Shanmuganathan M, Ali M, Alqifari S, Mani V, Dhanasekaran M, Alqahtani A, Alanazi M, Aljabri A. Sea Horse Optimization–Deep Neural Network: A Medication Adherence Monitoring System Based on Hand Gesture Recognition. Sensors 2024;24(16):5224 View