International journal of health geographics
Jul 25, 2019
BACKGROUND: Neighbourhood environment characteristics have been found to be associated with residents' willingness to conduct physical activity (PA). Traditional methods to assess perceived neighbourhood environment characteristics are often subjecti...
Nutritional phenotyping can help achieve personalized nutrition, and machine learning tools may offer novel means to achieve phenotyping. The primary aim of this study was to use energy balance components, namely input (dietary energy intake and macr...
Photoplethysmography (PPG)-based continuous heart rate monitoring is essential in a number of domains, e.g., for healthcare or fitness applications. Recently, methods based on time-frequency spectra emerged to address the challenges of motion artefac...
IEEE journal of biomedical and health informatics
May 20, 2019
PURPOSE: To evaluate and enhance the generalization performance of machine learning physical activity intensity prediction models developed with raw acceleration data on populations monitored by different activity monitors.
PURPOSE: This study investigated the effects of obesity on breast size, thoracic spine structure and function, upper torso musculoskeletal pain and physical activity participation in women living independently in the community.
BACKGROUND: Physical activity data provides important information on disease onset, progression, and treatment outcomes. Although analyzing physical activity data in conjunction with other clinical and microbiological data will lead to new insights c...
Accelerometers are commonly used in clinical and epidemiological research for more detailed measures of physical activity and to target the limitations of self-report methods. Sensors are attached at the hip, wrist and thigh, and the acceleration dat...
The physiological monitoring of older people using wearable sensors has shown great potential in improving their quality of life and preventing undesired events related to their health status. Nevertheless, creating robust predictive models from data...
We hypothesized that blood lactate concentration([Lac]) is a function of cardiopulmonary variables, exercise intensity and some anthropometric elements during aerobic exercise. This investigation aimed to establish a mathematical model to estimate [L...
Activity recognition using off-the-shelf smartwatches is an important problem in humanactivity recognition. In this paper, we present an end-to-end deep learning approach, able to provideprobability distributions over activities from raw sensor data....