AIMC Topic: Exercise

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Application of Raw Accelerometer Data and Machine-Learning Techniques to Characterize Human Movement Behavior: A Systematic Scoping Review.

Journal of physical activity & health
BACKGROUND: Application of machine learning for classifying human behavior is increasingly common as access to raw accelerometer data improves. The aims of this scoping review are (1) to examine if machine-learning techniques can accurately identify ...

Exercise cardiac power and the risk of heart failure in men: A population-based follow-up study.

Journal of sport and health science
BACKGROUND: Little is known about exercise cardiac power (ECP), defined as the ratio of directly measured maximal oxygen uptake with peak systolic blood pressure during exercise, on heart failure (HF) risk. We examined the association of ECP and the ...

Machine Learning Analysis for Quantitative Discrimination of Dried Blood Droplets.

Scientific reports
One of the most interesting and everyday natural phenomenon is the formation of different patterns after the evaporation of liquid droplets on a solid surface. The analysis of dried patterns from blood droplets has recently gained a lot of attention,...

Exercising with Baxter: preliminary support for assistive social-physical human-robot interaction.

Journal of neuroengineering and rehabilitation
BACKGROUND: The worldwide population of older adults will soon exceed the capacity of assisted living facilities. Accordingly, we aim to understand whether appropriately designed robots could help older adults stay active at home.

Performance Analysis of Boosting Classifiers in Recognizing Activities of Daily Living.

International journal of environmental research and public health
Physical activity is essential for physical and mental health, and its absence is highly associated with severe health conditions and disorders. Therefore, tracking activities of daily living can help promote quality of life. Wearable sensors in this...

A Multi-Modal Person Perception Framework for Socially Interactive Mobile Service Robots.

Sensors (Basel, Switzerland)
In order to meet the increasing demands of mobile service robot applications, a dedicated perception module is an essential requirement for the interaction with users in real-world scenarios. In particular, multi sensor fusion and human re-identifica...

Big Data Analytics and Sensor-Enhanced Activity Management to Improve Effectiveness and Efficiency of Outpatient Medical Rehabilitation.

International journal of environmental research and public health
Numerous societal trends are compelling a transition from inpatient to outpatient venues of care for medical rehabilitation. While there are advantages to outpatient rehabilitation (e.g., lower cost, more relevant to home and community function), the...

Profiling movement behaviours in pre-school children: A self-organised map approach.

Journal of sports sciences
Application of machine learning techniques has the potential to yield unseen insights into movement and permits visualisation of complex behaviours and tangible profiles. The aim of this study was to identify profiles of relative motor competence (MC...

Machine learning algorithms can classify outdoor terrain types during running using accelerometry data.

Gait & posture
BACKGROUND: Running is a popular physical activity that benefits health; however, running surface characteristics may influence loading impact and injury risk. Machine learning algorithms could automatically identify running surface from wearable mot...

A Multi-Mode Rehabilitation Robot With Magnetorheological Actuators Based on Human Motion Intention Estimation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Lower extremity paralysis has become common in recent years, and robots have been developed to help patients recover from it. This paper presents such a robotic system that allows for two working modes, the robot-active mode and human-active mode. Th...