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Exploring Remote Monitoring of Poststroke Mood With Digital Sensors by Assessment of Depression Phenotypes and Accelerometer Data in UK Biobank: Cross-Sectional Analysis

Exploring Remote Monitoring of Poststroke Mood With Digital Sensors by Assessment of Depression Phenotypes and Accelerometer Data in UK Biobank: Cross-Sectional Analysis

Blending self-reported assessments of phenomena, like mood, recorded through web browsers and smartphone apps, with passive sensor data, like that from wearable accelerometers, is gaining popularity in real-world settings [26,27]. Numerous pilot studies have demonstrated the potential for wearable and minimally invasive sensors to detect neurologic conditions; however, these tools have neither been validated in population cohorts nor combined with survey sampling of mood [28].

Stephanie J Zawada, Ali Ganjizadeh, Gian Marco Conte, Bart M Demaerschalk, Bradley J Erickson

JMIR Neurotech 2025;4:e56679

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

This inertial measurement unit ERGOtex sensor comprises 3 triaxial accelerometers (±2 g, controlled noise at 100 µg/√Hz), triaxial gyroscopes (±1000 deg/s, sensitivity error within ±1%, and low noise level, at ±4 mdeg/s/√Hz), and magnetometers, encapsulated in a device (weight=8 g, dimensions=23×21×10 mm). The ICM-20602 MEMS Motion Tracking (TDK Corp) device was selected for its high-performance specifications, critical for the reliability of the device.

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

JMIR Med Inform 2024;12:e57097

Studying Movement-Related Behavioral Maintenance and Adoption in Real Time: Protocol for an Intensive Ecological Momentary Assessment Study Among Older Adults

Studying Movement-Related Behavioral Maintenance and Adoption in Real Time: Protocol for an Intensive Ecological Momentary Assessment Study Among Older Adults

For the duration of each data collection period, waist-worn and thigh-worn accelerometers measure participants’ PA and SB, respectively. In addition, on days 9 to 12 of each data collection period, participants complete an EMA protocol in which they use a loaned smartphone to answer 10 brief questionnaires per day assessing current behavior, context, feeling states, demands, and motivation to engage in PA and limit SB over the next hour. Figure 1 provides an overview of the study’s design and procedures.

Jaclyn P Maher, Derek J Hevel, Kelsey M Bittel, Brynn L Hudgins, Jeffery D Labban, Laurie Kennedy-Malone

JMIR Res Protoc 2023;12:e47320

Comparison of the Validity and Generalizability of Machine Learning Algorithms for the Prediction of Energy Expenditure: Validation Study

Comparison of the Validity and Generalizability of Machine Learning Algorithms for the Prediction of Energy Expenditure: Validation Study

In general, an increase in training observations is considered a mechanism for enhancing performance [41], and the results of this study provide some evidence that this is the case in both commercial and research-grade accelerometers. Another strength of this study is the testing of numerous algorithm and device combinations.

Ruairi O'Driscoll, Jake Turicchi, Mark Hopkins, Cristiana Duarte, Graham W Horgan, Graham Finlayson, R James Stubbs

JMIR Mhealth Uhealth 2021;9(8):e23938

Effect and Process Evaluation of a Smartphone App to Promote an Active Lifestyle in Lower Educated Working Young Adults: Cluster Randomized Controlled Trial

Effect and Process Evaluation of a Smartphone App to Promote an Active Lifestyle in Lower Educated Working Young Adults: Cluster Randomized Controlled Trial

One week later, the research team returned to the workplaces to collect the accelerometers. During that second visit, participants in the intervention group were asked to download the Active Coach app on their smartphone, and they received a wearable activity tracker (ie, Fitbit Charge). They were asked to use the Active Coach app and the wearable activity tracker for the next 9 weeks.

Dorien Simons, Ilse De Bourdeaudhuij, Peter Clarys, Katrien De Cocker, Corneel Vandelanotte, Benedicte Deforche

JMIR Mhealth Uhealth 2018;6(8):e10003