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A Dual-Accelerometer System for Classifying Physical Activity in Children and Adults.

Medicine and science in sports and exercise
INTRODUCTION: Accurately monitoring 24-h movement behaviors is a vital step for progressing the time-use epidemiology field. Past accelerometer-based measurement protocols are either hindered by lack of wear time compliance, or the inability to accur...

Real-Time Human Physical Activity Recognition with Low Latency Prediction Feedback Using Raw IMU Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
In the realm of Human Activity Recognition (HAR), supervised machine learning and deep learning are commonly used. Their training is done using time and frequency features extracted from raw data (inertial and gyroscopic). Nevertheless, raw data are ...

Reduced Effort Does Not Imply Slacking: Responsiveness to Error Increases With Robotic Assistance.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
In both neurorehabilitation and functional augmentation, the patient or the user's muscular effort diminishes when the movement of their limb is supported by a robot. Is this relaxation a result of "slacking" by letting the robot take-over the moveme...

Improving Hip-Worn Accelerometer Estimates of Sitting Using Machine Learning Methods.

Medicine and science in sports and exercise
PURPOSE: This study aimed to improve estimates of sitting time from hip-worn accelerometers used in large cohort studies by using machine learning methods developed on free-living activPAL data.

Machine Learning in Rehabilitation Assessment for Thermal and Heart Rate Data Processing.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Multimodal signal analysis based on sophisticated noninvasive sensors, efficient communication systems, and machine learning, have a rapidly increasing range of different applications. The present paper is devoted to pattern recognition and the analy...

An Optimal Method of Training the Specific Lower Limb Muscle Group Using an Exoskeletal Robot.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
This paper suggests a novel method of strengthening specific muscle groups in the lower limb during a functional movement. When the foot of an user wearing an exoskeletal robot follows a given path, the contribution of each muscle group to generate t...

Robotic gaming prototype for upper limb exercise: Effects of age and embodiment on user preferences and movement.

Restorative neurology and neuroscience
BACKGROUND: Effective human-robot interactions in rehabilitation necessitates an understanding of how these should be tailored to the needs of the human. We report on a robotic system developed as a partner on a 3-D everyday task, using a gamified ap...

Novel Wearable Seismocardiography and Machine Learning Algorithms Can Assess Clinical Status of Heart Failure Patients.

Circulation. Heart failure
BACKGROUND: Remote monitoring of patients with heart failure (HF) using wearable devices can allow patient-specific adjustments to treatments and thereby potentially reduce hospitalizations. We aimed to assess HF state using wearable measurements of ...

Salivary Markers for Quantitative Dehydration Estimation During Physical Exercise.

IEEE journal of biomedical and health informatics
Salivary markers have been proposed as noninvasive and easy-to-collect indicators of dehydrations during physical exercise. It has been demonstrated that threshold-based classifications can distinguish dehydrated from euhydrated subjects. However, co...