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Accelerometry-Assessed Physical Activity and Circadian Rhythm to Detect Clinical Disability Status in Multiple Sclerosis: Cross-Sectional Study

Accelerometry-Assessed Physical Activity and Circadian Rhythm to Detect Clinical Disability Status in Multiple Sclerosis: Cross-Sectional Study

Several studies have looked at the use of accelerometry in MS to identify associations with sleep, fatigue, depression, or disability outcomes (EDSS and Patient-Determined Disease Steps); however, whether wrist-worn accelerometry can differentiate between people with RRMS and PMS remains an existing question [8-16]. We hypothesized that people with RRMS and PMS have different physical activity and circadian rhythmicity patterns.

Nicole Bou Rjeily, Muraleetharan Sanjayan, Pratim Guha Niyogi, Blake E Dewey, Alexandra Zambriczki Lee, Christy Hulett, Gabriella Dagher, Chen Hu, Rafal D Mazur, Elena M Kenney, Erin Brennan, Anna DuVal, Peter A Calabresi, Vadim Zipunnikov, Kathryn C Fitzgerald, Ellen M Mowry

JMIR Mhealth Uhealth 2025;13:e57599

Combining Ecological Momentary Assessment and Social Network Analysis to Study Youth Physical Activity and Environmental Influences: Protocol for a Mixed Methods Feasibility Study

Combining Ecological Momentary Assessment and Social Network Analysis to Study Youth Physical Activity and Environmental Influences: Protocol for a Mixed Methods Feasibility Study

Moreover, the frequent prompts and awareness of being monitored could introduce reactivity, where participants alter their behavior or reporting patterns, while the complexity of the data collected across multiple platforms (EMA, GPS, and accelerometry) presents substantial challenges in data integration, cleaning, and analysis, requiring sophisticated statistical approaches to handle the multilevel, time-varying nature of the data.

Tyler Prochnow, Genevieve F Dunton, Kayla de la Haye, Keshia M Pollack Porter, Chanam Lee

JMIR Res Protoc 2025;14:e68667

Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study

Analysis of Physical Activity Using Wearable Health Technology in US Adults Enrolled in the All of Us Research Program: Multiyear Observational Study

This alignment was observed both in self-reported data and data derived from accelerometry [9,10,12,45,48]. We found that women were significantly less physically active than men. Although further research is needed to fully understand this phenomenon, existing studies suggest that various factors contribute to lower PA participation among women.

Rujul Singh, Macy K Tetrick, James L Fisher, Peter Washington, Jane Yu, Electra D Paskett, Frank J Penedo, Steven K Clinton, Roberto M Benzo

J Med Internet Res 2024;26:e65095

Raw Photoplethysmography as an Enhancement for Research-Grade Wearable Activity Monitors

Raw Photoplethysmography as an Enhancement for Research-Grade Wearable Activity Monitors

Intermonitor differences and lack of flexibility are thus limitations of current standards for PPG, in much the same way as they once were for accelerometry. Furthermore, concerns have frequently been raised about unannounced algorithm and firmware updates that can make consumer-grade technology undesirable in certain research contexts [77-81].

Paul R Hibbing, Maryam Misal Khan

JMIR Mhealth Uhealth 2024;12:e57158

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

For a better understanding of the data and selection of the hyperparameters of the AI model, the accelerometry and gyroscope values of each movement were analyzed separately (Figure 8). Based on this, the temporal sequences were divided into windows of 100 records with a 10-record overlap between adjacent windows. Time series of eating activity: (A) accelerometer and (B) gyroscope. Each model was trained over 150 epochs, representing a complete iteration through the training data.

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

JMIR Med Inform 2024;12:e57097

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

Wearable Sensor Technologies to Assess Motor Functions in People With Multiple Sclerosis: Systematic Scoping Review and Perspective

Databases searched up to December 31, 2022, without language restrictions Pub Med Scopus Embase Web of Science Search terms "multiple sclerosis" AND ("smartphone" OR "smartphones" OR "smartwatch" OR "smartwatches" OR "wearable" OR "wearables" OR "biosensor" OR "biosensors" OR "digital biomarker" OR "digital biomarkers" OR "accelerometer" OR "accelerometers" OR "accelerometry" OR "gyroscope" OR "gyroscopes" OR "inertial motion unit" OR "IMU") Article types Included articles Peer-reviewed conference papers Peer-reviewed

Tim Woelfle, Lucie Bourguignon, Johannes Lorscheider, Ludwig Kappos, Yvonne Naegelin, Catherine Ruth Jutzeler

J Med Internet Res 2023;25:e44428

A Trainable Open-Source Machine Learning Accelerometer Activity Recognition Toolbox: Deep Learning Approach

A Trainable Open-Source Machine Learning Accelerometer Activity Recognition Toolbox: Deep Learning Approach

Accelerometry-based behavior analysis has a variety of applications, such as fall detection in older patients [3], health monitoring [4], work-related stress analysis [5], and sleep analysis [6]. The widespread use of accelerometry in everyday smartphone apps has reduced the cost of gyroscope and accelerometer sensors, which has in turn accelerated their development. While wearables have gained popularity as accelerometer devices, smartphones still make up the majority of them.

Fluri Wieland, Claudio Nigg

JMIR AI 2023;2:e42337

Accelerometer-Measured Inpatient Physical Activity and Associated Outcomes After Major Abdominal Surgery: Systematic Review

Accelerometer-Measured Inpatient Physical Activity and Associated Outcomes After Major Abdominal Surgery: Systematic Review

The search strategy included the Medical Subject Headings (Me SH) terms “postoperative period,” “postoperative care,” “accelerometry,” “wearable electronic devices,” “fitness trackers,” and their related terms (Multimedia Appendix 2). The database included all publications up to October 14, 2021. For Google Scholar, we screened the first 100 articles as described previously [16]. Reference lists of related studies were also used to identify relevant articles.

Mikita Fuchita, Kyle J Ridgeway, Clinton Kimzey, Edward L Melanson, Ana Fernandez-Bustamante

Interact J Med Res 2023;12:e46629