ArticleSensors (Basel, Switzerland)2019
Evaluation of Inertial Sensor-Based Pre-Impact Fall Detection Algorithms Using Public Dataset.
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 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Functional autonomy in dementia of the Alzheimer's type, mild cognitive impairment, and healthy aging: a meta-analysis.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021Pooled it
- A Comparative Overview of Technological Advances in Fall Detection Systems for Elderly People.Sensors (Basel, Switzerland) · 2025Article
- An Effective Deep Learning Framework for Fall Detection: Model Development and Study Design.Journal of medical Internet research · 2024Article
- TinyFallNet: A Lightweight Pre-Impact Fall Detection Model.Sensors (Basel, Switzerland) · 2023Article
- Fall Detection Algorithm Based on Inertial Sensor and Hierarchical Decision.Sensors (Basel, Switzerland) · 2022Article
- Gait Trajectory Prediction on an Embedded Microcontroller Using Deep Learning.Sensors (Basel, Switzerland) · 2022Article
- Smart Wearables with Sensor Fusion for Fall Detection in Firefighting.Sensors (Basel, Switzerland) · 2021Article
- A Hierarchical Approach to Activity Recognition and Fall Detection Using Wavelets and Adaptive Pooling.Sensors (Basel, Switzerland) · 2021Article
- Article
- Pre-Impact Fall Detection with CNN-Based Class Activation Mapping Method.Sensors (Basel, Switzerland) · 2020Article
- Enhanced Algorithm for the Detection of Preimpact Fall for Wearable Airbags.Sensors (Basel, Switzerland) · 2020Article
- A Novel Hybrid Deep Neural Network to Predict Pre-impact Fall for Older People Based on Wearable Inertial Sensors.Frontiers in bioengineering and biotechnology · 2020Article
- Effects of Combined Balance and Strength Training on Measures of Balance and Muscle Strength in Older Women With a History of Falls.Frontiers in physiology · 2020Article
- A Smart Robotic Walker With Intelligent Close-Proximity Interaction Capabilities for Elderly Mobility Safety.Frontiers in neurorobotics · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this study, pre-impact fall detection algorithms were developed based on data gathered by a custom-made inertial measurement unit (IMU). Four types of simulated falls were performed by 40 healthy subjects (age: 23.4 ± 4.4 years). The IMU recorded acceleration and angular velocity during all activities. Acceleration, angular velocity, and trunk inclination thresholds were set to 0.9 g, 47.3°/s, and 24.7°, respectively, for a pre-impact fall detection algorithm using vertical angles (VA algorithm); and 0.9 g, 47.3°/s, and 0.19, respectively, for an algorithm using the triangle feature (TF algorithm). The algorithms were validated by the results of a blind test using four types of simulated falls and six types of activities of daily living (ADL). VA and TF algorithms resulted in lead times of 401 ± 46.9 ms and 427 ± 45.9 ms, respectively. Both algorithms were able to detect falls with 100% accuracy. The performance of the algorithms was evaluated using a public dataset. Both algorithms detected every fall in the SisFall dataset with 100% sensitivity). The VA algorithm had a specificity of 78.3%, and TF algorithm had a specificity of 83.9%. The algorithms had higher specificity when interpreting data from elderly subjects. This study showed that algorithms using angles could more accurately detect falls. Public datasets are needed to improve the accuracy of the algorithms.
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Registered trials
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