AIMC Topic: Exercise

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Hierarchical classification scheme for real-time recognition of physical activities and postural transitions using smartphone inertial sensors.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This paper introduces a novel approach for real-time classification of human activities using data from inertial sensors embedded in a smartphone. We propose a hierarchical classification scheme to recognize seven classes of activities including post...

Physical Activity Change in an RCT: Comparison of Measurement Methods.

American journal of health behavior
We aimed to quantify the agreement between self-report, standard cut-point accelerometer, and machine learning accelerometer estimates of physical activity (PA), and exam- ine how agreement changes over time among older adults in an intervention set...

Characteristics of Transactive Relationship Phenomena among Older adults, Care Workers as Intermediaries, and the Pepper Robot with Care Prevention Gymnastics Exercises.

The journal of medical investigation : JMI
Healthcare for older adults is a significant problem in Japan and in other developed countries. To address this problem, healthcare robots, now realized, can assist and meet healthcare and welfare practice demands. The aim of this study was to clarif...

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...