ReviewSensors (Basel, Switzerland)2022
Human Activity Recognition Data Analysis: History, Evolutions, and New Trends.
Review in Sensors (Basel, Switzerland), 2022. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Transfer and Reinforcement Learning as Support Paradigms for Human Activity Recognition in Indoor Environments: A Comprehensive Analysis of Trends, Impact and Future Directions.Sensors (Basel, Switzerland) · 2026Review
- Adaptive temporal attention mechanism and hybrid deep CNN model for wearable sensor-based human activity recognition.Scientific reports · 2025Article
- SmartAPM framework for adaptive power management in wearable devices using deep reinforcement learning.Scientific reports · 2025Article
- A Multi-Agent and Attention-Aware Enhanced CNN-BiLSTM Model for Human Activity Recognition for Enhanced Disability Assistance.Diagnostics (Basel, Switzerland) · 2025Article
- An improved human activity recognition technique based on convolutional neural network.Scientific reports · 2023Article
- Human Activity Recognition via Score Level Fusion of Wi-Fi CSI Signals.Sensors (Basel, Switzerland) · 2023Article
- Exploring Regularization Methods for Domain Generalization in Accelerometer-Based Human Activity Recognition.Sensors (Basel, Switzerland) · 2023Article
- Induction Motor Fault Diagnosis Using Support Vector Machine, Neural Networks, and Boosting Methods.Sensors (Basel, Switzerland) · 2023Article
- Comparing Handcrafted Features and Deep Neural Representations for Domain Generalization in Human Activity Recognition.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Assisted Living Environments Research Area-AAL (Ambient Assisted Living), focuses on generating innovative technology, products, and services to assist, medical care and rehabilitation to older adults, to increase the time in which these people can live. independently, whether they suffer from neurodegenerative diseases or some disability. This important area is responsible for the development of activity recognition systems-ARS (Activity Recognition Systems), which is a valuable tool when it comes to identifying the type of activity carried out by older adults, to provide them with assistance. that allows you to carry out your daily activities with complete normality. This article aims to show the review of the literature and the evolution of the different techniques for processing this type of data from supervised, unsupervised, ensembled learning, deep learning, reinforcement learning, transfer learning, and metaheuristics approach applied to this sector of science. health, showing the metrics of recent experiments for researchers in this area of knowledge. As a result of this article, it can be identified that models based on reinforcement or transfer learning constitute a good line of work for the processing and analysis of human recognition activities.
Indexed as
Identifiers
What OpenQuestion holds
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.