ArticleSensors (Basel, Switzerland)2018
Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
9 citing papers in PubMed.
- Smart Sensing Technology for Human Activity Recognition.Sensors (Basel, Switzerland) · 2026Article
- A Review on Assisted Living Using Wearable Devices.Sensors (Basel, Switzerland) · 2024Review
- The Relationship Between the Burpee Movement Program and Strength and Endurance Performance Measures in Active Young Adults: A Cross-Sectional Analysis.Journal of functional morphology and kinesiology · 2024Article
- Multilevel attention mechanism for motion fatigue recognition based on sEMG and ACC signal fusion.PloS one · 2024Article
- Analysis of the Hanging Actions and Operating Heights of Storage Furniture Suitable for the Elderly.Sensors (Basel, Switzerland) · 2023Article
- Energy and Performance Analysis of Lossless Compression Algorithms for Wireless EMG Sensors.Sensors (Basel, Switzerland) · 2021Article
- Hardware for Recognition of Human Activities: A Review of Smart Home and AAL Related Technologies.Sensors (Basel, Switzerland) · 2020Review
- Hand-Gesture Recognition Based on EMG and Event-Based Camera Sensor Fusion: A Benchmark in Neuromorphic Computing.Frontiers in neuroscience · 2020Article
- A Comparative Study of Computational Methods for Compressed Sensing Reconstruction of EMG Signal.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The human activity diarization using wearable technologies is one of the most important supporting techniques for ambient assisted living, sport and fitness activities, healthcare of elderly people. The activity diarization is performed in two steps: the acquisition of body signals and the classification of activities being performed. This paper presents a technique for data fusion at classifier level of accelerometer and sEMG signals acquired by using a low-cost wearable wireless system for monitoring the human activity when performing sport and fitness activities, as well as in healthcare applications. To demonstrate the capability of the system of diarizing the user's activities, data recorded from a few subjects were used to train and test the automatic classifier for recognizing the type of exercise being performed.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.