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The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review

The Use of Artificial Intelligence and Wearable Inertial Measurement Units in Medicine: Systematic Review

Pub Med yielded 327 articles with the search string: (“Artificial Intelligence”[Mesh]) AND (health OR medical OR clinical OR patient) AND (wearabl* OR smartphone OR smartwatch) AND (magnetometer OR accelerom* OR gyroscope OR “imu” OR “imus” OR “Inertial measurement unit”) AND (health OR medical OR clinical OR patient) NOT (Review[Publication Type] OR Systematic Review[Publication Type]).

Ricardo Smits Serena, Florian Hinterwimmer, Rainer Burgkart, Rudiger von Eisenhart-Rothe, Daniel Rueckert

JMIR Mhealth Uhealth 2025;13:e60521

Recognition of Daily Activities in Adults With Wearable Inertial Sensors: Deep Learning Methods Study

Recognition of Daily Activities in Adults With Wearable Inertial Sensors: Deep Learning Methods Study

The signals collected by the accelerometer and gyroscope were used to train a 1 D convolutional neural network–based feature learning model, enabling the identification of 6 ADL. The results demonstrated high accuracy in both external and study data, validating the effectiveness of the proposed method. The study by Huynh-The et al [41] introduces an innovative method for recognizing ADL- and sports-related activities using wearable sensors.

Alberto De Ramón Fernández, Daniel Ruiz Fernández, Miguel García Jaén, Juan M. Cortell-Tormo

JMIR Med Inform 2024;12:e57097

An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design

An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design

Consequently, researchers advocate for the integration of acceleration data with gyroscope data to provide a more comprehensive understanding of body movements, which can significantly enhance the accuracy of fall detection [30,31]. In this case, Hussain et al [32], Son et al [33], Liu et al [34], and Koo et al [35] use acceleration data with gyroscope data as the input to the model.

Jinxi Zhang, Zhen Li, Yu Liu, Jian Li, Hualong Qiu, Mohan Li, Guohui Hou, Zhixiong Zhou

J Med Internet Res 2024;26:e56750

Inertial Measurement Units and Application for Remote Health Care in Hip and Knee Osteoarthritis: Narrative Review

Inertial Measurement Units and Application for Remote Health Care in Hip and Knee Osteoarthritis: Narrative Review

Using a robotic arm and anthropomorphic leg phantom to simulate knee flexion at 3 different speeds, Fennema et al [16] identified acceptable test-retest repeatability of IMU-based joint angle measurements ( Inertial sensors validity and reliability measuring movement. a THA: total hip arthroplasty. b TKA: total knee arthroplasty. c IMU: inertial measurement unit (with accelerometer, gyroscope, and magnetometer). d OA: osteoarthritis. e IMU with accelerometer and gyroscope.

Michael J. Rose, Kerry E Costello, Samantha Eigenbrot, Kaveh Torabian, Deepak Kumar

JMIR Rehabil Assist Technol 2022;9(2):e33521

Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants’ Well-being: Ecological Momentary Assessment

Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants’ Well-being: Ecological Momentary Assessment

We collected sensor readings from the accelerometer and gyroscope alongside an unrelated EMA study. Participants in this study were 158 employees who were recruited to report on factors pertaining to their work-related stress and after-work detachment 6 days a week for 3 weeks. We then used those data to train machine learning models on the first 13 mornings of the data collection period to infer all of a participant’s self-reported states on the last 5 mornings based on the sensor data from these days.

Alexander Hart, Dorota Reis, Elisabeth Prestele, Nicholas C Jacobson

J Med Internet Res 2022;24(4):e34015

A Wearable Ballistocardiography Device for Estimating Heart Rate During Positive Airway Pressure Therapy: Investigational Study Among the General Population

A Wearable Ballistocardiography Device for Estimating Heart Rate During Positive Airway Pressure Therapy: Investigational Study Among the General Population

The mask was a Res Med Quattro Air mask, onto which an IMU (MPU 9150; Invensense), which includes a 3-axes gyroscope signal, was attached, as shown in Figure 1. The configuration of the gyroscope was such that x rotation corresponded to rotating the head from left to right, y rotation corresponded to head tilt toward the shoulders, and z rotation corresponded to a nodding up and down movement. Position and orientation of the gyroscope on a positive airway pressure mask.

Mark Gardner, Sharmil Randhawa, Gordon Malouf, Karen Reynolds

JMIR Cardio 2021;5(1):e26259