Approaching the real-world: Supporting activity recognition training with virtual imu data

H Kwon, B Wang, GD Abowd, T Plötz - … of the ACM on Interactive, Mobile …, 2021 - dl.acm.org
Recently, IMUTube introduced a paradigm change for bootstrap** human activity
recognition (HAR) systems for wearables. The key idea is to utilize videos of activities to …

Video based exercise recognition and correct pose detection

T Rangari, S Kumar, PP Roy, DP Dogra… - Multimedia Tools and …, 2022 - Springer
Human pose estimation has gained significant attention from researchers of the present era.
Personal exercise sessions can be monitored and supervised with the help of pose …

A survey of human action recognition using accelerometer data

A Mimouna, A Ben Khalifa - Advanced Sensors for Biomedical …, 2021 - Springer
Recognizing human actions and analyzing human behaviors from accelerometer data has
become a challenging task. Hence, Human Action Recognition (HAR) using inertial sensors …

Recognition and repetition counting for local muscular endurance exercises in exercise-based rehabilitation: A comparative study using artificial intelligence models

G Prabhu, NE O'connor, K Moran - Sensors, 2020 - mdpi.com
Exercise-based cardiac rehabilitation requires patients to perform a set of certain prescribed
exercises a specific number of times. Local muscular endurance exercises are an important …

Characterization of a wearable system for automatic supervision of fitness exercises

C Crema, A Depari, A Flammini, E Sisinni… - Measurement, 2019 - Elsevier
It is widely known that physical activity is an effective tool for preventing several diseases.
However, unsupervised training may lead to poor execution quality, resulting in ineffective …

Development of ai algorithm for weight training using inertial measurement units

YC Wu, SX Lin, JY Lin, CC Han, CS Chang, JX Jiang - Applied Sciences, 2022 - mdpi.com
Featured Application Fitness, Weight Training, Medical Rehabilitation, Sport Training, Health
Management. Abstract Thanks to the rapid development of Wearable Fitness Trackers …

Lightweight machine learning-based approach for supervision of fitness workout

A Depari, P Ferrari, A Flammini… - 2019 IEEE Sensors …, 2019 - ieeexplore.ieee.org
It is widely known that physical activity helps preventing several diseases. However,
unsupervised training often results in low exercise quality, ineffective training, and, in worst …

Intelligent Repetition Counting for Unseen Exercises: A Few-Shot Learning Approach with Sensor Signals

Y Lim, S Lee - arxiv preprint arxiv:2410.00407, 2024 - arxiv.org
Sensing technology has significantly advanced in automating systems that reflect human
movement, particularly in robotics and healthcare, where it is used to automatically detect …

The contribution of human body capacitance/body-area electric field to individual and collaborative activity recognition

S Bian, VF Rey, S Yuan, P Lukowicz - arxiv preprint arxiv:2210.14794, 2022 - arxiv.org
The current dominated wearable body motion sensor is IMU. This work presented an
alternative wearable motion-sensing approach: human body capacitance (HBC, also …

DeepPose: An Integrated Deep Learning Model for Posture Detection Using Image and Skeletal Data

M Singh, MSA Ansari, MC Govil - 2023 14th International …, 2023 - ieeexplore.ieee.org
Identifying human actions and postures presents significant challenges for computerized
systems. The categorization of these tasks holds particular relevance in the fields of health …