[HTML][HTML] Physical human activity recognition using wearable sensors
This paper presents a review of different classification techniques used to recognize human
activities from wearable inertial sensor data. Three inertial sensor units were used in this …
activities from wearable inertial sensor data. Three inertial sensor units were used in this …
Multi-sensor fusion for activity recognition—A survey
In Ambient Intelligence (AmI), the activity a user is engaged in is an essential part of the
context, so its recognition is of paramount importance for applications in areas like sports …
context, so its recognition is of paramount importance for applications in areas like sports …
A comparative study on human activity recognition using inertial sensors in a smartphone
A Wang, G Chen, J Yang, S Zhao… - IEEE Sensors …, 2016 - ieeexplore.ieee.org
Activity recognition plays an essential role in bridging the gap between the low-level sensor
data and the high-level applications in ambient-assisted living systems. With the aim to …
data and the high-level applications in ambient-assisted living systems. With the aim to …
Improving activity recognition accuracy in ambient-assisted living systems by automated feature engineering
Ambient-assisted living (AAL) is promising to become a supplement of the current care
models, providing enhanced living experience to people within context-aware homes and …
models, providing enhanced living experience to people within context-aware homes and …
How accurately can your wrist device recognize daily activities and detect falls?
Although wearable accelerometers can successfully recognize activities and detect falls,
their adoption in real life is low because users do not want to wear additional devices. A …
their adoption in real life is low because users do not want to wear additional devices. A …
Shoulder physiotherapy exercise recognition: machine learning the inertial signals from a smartwatch
DM Burns, N Leung, M Hardisty… - Physiological …, 2018 - iopscience.iop.org
Objective: Participation in a physical therapy program is considered one of the greatest
predictors of successful conservative management of common shoulder disorders. However …
predictors of successful conservative management of common shoulder disorders. However …
Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls
Current practice of assessing mood episodes in affective disorders largely depends on
subjective observations combined with semi-structured clinical rating scales. Motor activity is …
subjective observations combined with semi-structured clinical rating scales. Motor activity is …
A multimodal data processing system for LiDAR-based human activity recognition
Increasingly, the task of detecting and recognizing the actions of a human has been
delegated to some form of neural network processing camera or wearable sensor data. Due …
delegated to some form of neural network processing camera or wearable sensor data. Due …
Physiotherapy exercise classification with single-camera pose detection and machine learning
Access to healthcare, including physiotherapy, is increasingly occurring through virtual
formats. At-home adherence to physical therapy programs is often poor and few tools exist to …
formats. At-home adherence to physical therapy programs is often poor and few tools exist to …
Human activity recognition for production and logistics—a systematic literature review
This contribution provides a systematic literature review of Human Activity Recognition for
Production and Logistics. An initial list of 1243 publications that complies with predefined …
Production and Logistics. An initial list of 1243 publications that complies with predefined …