ArticleSensors (Basel, Switzerland)2020
Inertial Sensor-Based Instrumented Cane for Real-Time Walking Cane Kinematics Estimation.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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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.
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Who cites it
5 citing papers in PubMed, 12 citations in OpenAlex.
- Personalized Detection of Functional-State Changes Through Continuous Gait Monitoring: A Methodology for Assistive-Device Users.Sensors (Basel, Switzerland) · 2026Article
- Real-Time Estimation of Lower Limb Posture and Joint Angles Using Wearable IMUs: Reproduced Hemiparetic and Normal Gait.Japanese journal of comprehensive rehabilitation science · 2025Article
- Motion Capture Technologies for Ergonomics: A Systematic Literature Review.Diagnostics (Basel, Switzerland) · 2023Review
- Energy-Accuracy Aware Finger Gesture Recognition for Wearable IoT Devices.Sensors (Basel, Switzerland) · 2022Article
- Generation of Gait Events with a FSR Based Cane Handle.Sensors (Basel, Switzerland) · 2021Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Falls are among the main causes of injuries in elderly individuals. Balance and mobility impairment are major indicators of fall risk in this group. The objective of this research was to develop a fall risk feedback system that operates in real time using an inertial sensor-based instrumented cane. Based on inertial sensor data, the proposed system estimates the kinematics (contact phase and orientation) of the cane. First, the contact phase of the cane was estimated by a convolutional neural network. Next, various algorithms for the cane orientation estimation were compared and validated using an optical motion capture system. The proposed cane contact phase prediction model achieved higher accuracy than the previous models. In the cane orientation estimation, the Madgwick filter yielded the best results overall. Finally, the proposed system was able to estimate both the contact phase and orientation in real time in a single-board computer.
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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.