ArticleSensors (Basel, Switzerland)2017
Highly Portable, Sensor-Based System for Human Fall Monitoring.
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 99 citations in OpenAlex.
- Developing a smartphone application, triaxial accelerometer-based, to quantify static and dynamic balance deficits in patients with cerebellar ataxias.Journal of neurology · 2020Trial
- Article
- Quantifying shoulder motion in the free-living environment using wearable inertial measurement units: Challenges and recommendations.Journal of biomechanics · 2025Review
- Development and control of a robotic assistant walking aid for fall risk reduction.Frontiers in robotics and AI · 2025Article
- CNN-Based Self-Attention Weight Extraction for Fall Event Prediction Using Balance Test Score.Sensors (Basel, Switzerland) · 2023Article
- Fall Recognition Based on an IMU Wearable Device and Fall Verification through a Smart Speaker and the IoT.Sensors (Basel, Switzerland) · 2023Article
- An Ultrasonic-Based Sensor System for Elderly Fall Monitoring in a Smart Room.Journal of healthcare engineering · 2022Article
- Support Vector Machine Classifiers Show High Generalizability in Automatic Fall Detection in Older Adults.Sensors (Basel, Switzerland) · 2021Article
- A New Prototype of Smart Wearable Monitoring System Solution for Alzheimer's Patients.Medical devices (Auckland, N.Z.) · 2021Article
- Image Processing Technique and Hidden Markov Model for an Elderly Care Monitoring System.Journal of imaging · 2020Article
- Smart Environments and Social Robots for Age-Friendly Integrated Care Services.International journal of environmental research and public health · 2020Article
- Sensor-Based Smart Clothing for Women's Menopause Transition Monitoring.Sensors (Basel, Switzerland) · 2020Article
- Consumption Analysis of Smartphone based Fall Detection Systems with Multiple External Wireless Sensors.Sensors (Basel, Switzerland) · 2020Article
- Home-based monitoring of falls using wearable sensors in Parkinson's disease.Movement disorders : official journal of the Movement Disorder Society · 2020Article
- A Survey on Recent Advances in Wearable Fall Detection Systems.BioMed research international · 2020Review
- Detection of Human Fall Using Floor Vibration and Multi-Features Semi-Supervised SVM.Sensors (Basel, Switzerland) · 2019Article
- A New Approach to Fall Detection Based on Improved Dual Parallel Channels Convolutional Neural Network.Sensors (Basel, Switzerland) · 2019Article
- Review on Wearable Technology Sensors Used in Consumer Sport Applications.Sensors (Basel, Switzerland) · 2019Review
- Feature Representation and Data Augmentation for Human Activity Classification Based on Wearable IMU Sensor Data Using a Deep LSTM Neural Network.Sensors (Basel, Switzerland) · 2018Article
- A User-Adaptive Algorithm for Activity Recognition Based on K-Means Clustering, Local Outlier Factor, and Multivariate Gaussian Distribution.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Falls are a very dangerous situation especially among elderly people, because they may lead to fractures, concussion, and other injuries. Without timely rescue, falls may even endanger their lives. The existing optical sensor-based fall monitoring systems have some disadvantages, such as limited monitoring range and inconvenience to carry for users. Furthermore, the fall detection system based only on an accelerometer often mistakenly determines some activities of daily living (ADL) as falls, leading to low accuracy in fall detection. We propose a human fall monitoring system consisting of a highly portable sensor unit including a triaxis accelerometer, a triaxis gyroscope, and a triaxis magnetometer, and a mobile phone. With the data from these sensors, we obtain the acceleration and Euler angle (yaw, pitch, and roll), which represents the orientation of the user's body. Then, a proposed fall detection algorithm was used to detect falls based on the acceleration and Euler angle. With this monitoring system, we design a series of simulated falls and ADL and conduct the experiment by placing the sensors on the shoulder, waist, and foot of the subjects. Through the experiment, we re-identify the threshold of acceleration for accurate fall detection and verify the best body location to place the sensors by comparing the detection performance on different body segments. We also compared this monitoring system with other similar works and found that better fall detection accuracy and portability can be achieved by our system.
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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.