ArticleSensors (Basel, Switzerland)2019
Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers.
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Who cites it
54 citing papers in PubMed.
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- Placement-Dependent Accuracy of a Smartphone-Based Sensor Application Compared to an Accelerometer-Based System for Measuring Physical Activity in Healthy Adults: A Validation Study.Sensors (Basel, Switzerland) · 2026Article
- Multimodal machine learning mobility assessment in Parkinson's disease within supervised and unsupervised settings.Journal of neuroengineering and rehabilitation · 2026Article
- Assessment of gait speed in older adults using a short-distance walking test with smartphone motion sensors and machine learning.Scientific reports · 2025Article
- An Improved Step Detection Algorithm for Indoor Navigation Problems with Pre-Determined Types of Activity.Sensors (Basel, Switzerland) · 2025Article
- Indoor Positioning Systems as Critical Infrastructure: An Assessment for Enhanced Location-Based Services.Sensors (Basel, Switzerland) · 2025Review
- Recent Advancements in Rubber Composites for Physical Activity Monitoring Sensors: A Critical Review.Polymers · 2025Review
- Automated Pipeline for Robust Cat Activity Detection Based on Deep Learning and Wearable Sensor Data.Sensors (Basel, Switzerland) · 2024Article
- Exploring the Impact of theSensors (Basel, Switzerland) · 2024Article
- Enhancing public health in developing nations through smartphone-based motor assessment.Frontiers in digital health · 2024Article
- Empowering Participatory Research in Urban Health: Wearable Biometric and Environmental Sensors for Activity Recognition.Sensors (Basel, Switzerland) · 2023Article
- A Multi-Layer Classifier Model XR-KS of Human Activity Recognition for the Problem of Similar Human Activity.Sensors (Basel, Switzerland) · 2023Article
- Exploring Regularization Methods for Domain Generalization in Accelerometer-Based Human Activity Recognition.Sensors (Basel, Switzerland) · 2023Article
- New Method for Reduced-Number IMU Estimation in Observing Human Joint Motion.Sensors (Basel, Switzerland) · 2023Article
- Effect of Equipment on the Accuracy of Accelerometer-Based Human Activity Recognition in Extreme Environments.Sensors (Basel, Switzerland) · 2023Article
- Artificial Intelligence Based Approach for Classification of Human Activities Using MEMS Sensors Data.Sensors (Basel, Switzerland) · 2023Article
- Guided regularized random forest feature selection for smartphone based human activity recognition.Journal of ambient intelligence and humanized computing · 2023Article
- Human behavior recognition based on sparse transformer with channel attention mechanism.Frontiers in physiology · 2023Article
- Ambient assisted living for frail people through human activity recognition: state-of-the-art, challenges and future directions.Frontiers in neuroscience · 2023Review
- Less is more: Efficient behavioral context recognition using Dissimilarity-Based Query Strategy.PloS one · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ubiquity of smartphones and the growth of computing resources, such as connectivity, processing, portability, and power of sensing, have greatly changed people's lives. Today, many smartphones contain a variety of powerful sensors, including motion, location, network, and direction sensors. Motion or inertial sensors (e.g., accelerometer), specifically, have been widely used to recognize users' physical activities. This has opened doors for many different and interesting applications in several areas, such as health and transportation. In this perspective, this work provides a comprehensive, state of the art review of the current situation of human activity recognition (HAR) solutions in the context of inertial sensors in smartphones. This article begins by discussing the concepts of human activities along with the complete historical events, focused on smartphones, which shows the evolution of the area in the last two decades. Next, we present a detailed description of the HAR methodology, focusing on the presentation of the steps of HAR solutions in the context of inertial sensors. For each step, we cite the main references that use the best implementation practices suggested by the scientific community. Finally, we present the main results about HAR solutions from the perspective of the inertial sensors embedded in smartphones.
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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.