Synchronized Sensor Insoles for Clinical Gait Analysis in Home-Monitoring Applications
Wearable sensor systems are of increasing interest in clinical gait analysis. However, little information about gait dynamics of patients under free living conditions is available, due to the challenges of integrating such systems unobtrusively into a patient’s everyday live. To address this limitat...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2018-09-01
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| Series: | Current Directions in Biomedical Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/cdbme-2018-0103 |
| _version_ | 1797740385389248512 |
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| author | Roth Nils Martindale Christine F. Eskofier Bjoern M. Gaßner Heiko Kohl Zacharias Klucken Jochen |
| author_facet | Roth Nils Martindale Christine F. Eskofier Bjoern M. Gaßner Heiko Kohl Zacharias Klucken Jochen |
| author_sort | Roth Nils |
| collection | DOAJ |
| description | Wearable sensor systems are of increasing interest in clinical gait analysis. However, little information about gait dynamics of patients under free living conditions is available, due to the challenges of integrating such systems unobtrusively into a patient’s everyday live. To address this limitation, new, fully integrated low power sensor insoles are proposed, to target applications particularly in home-monitoring scenarios. The insoles combine inertial as well as pressure sensors and feature wireless synchronization to acquire biomechanical data of both feet with a mean timing offset of 15.0 μs. The proposed system was evaluated on 15 patients with mild to severe gait disorders against the GAITRite® system as reference. Gait events based on the insoles’ pressure sensors were manually extracted to calculate temporal gait features such as double support time and double support. Compared to the reference system a mean error of 0.06 s ±0.06 s and 3.89 % ±2.61 % was achieved, respectively. The proposed insoles proved their ability to acquire synchronized gait parameters and address the requirements for home-monitoring scenarios, pushing the boundaries of clinical gait analysis. |
| first_indexed | 2024-03-12T14:11:41Z |
| format | Article |
| id | doaj.art-759ddaa13b7647018a346fd4df9d0f08 |
| institution | Directory Open Access Journal |
| issn | 2364-5504 |
| language | English |
| last_indexed | 2024-03-12T14:11:41Z |
| publishDate | 2018-09-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Current Directions in Biomedical Engineering |
| spelling | doaj.art-759ddaa13b7647018a346fd4df9d0f082023-08-21T06:42:02ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042018-09-014143343710.1515/cdbme-2018-0103cdbme-2018-0103Synchronized Sensor Insoles for Clinical Gait Analysis in Home-Monitoring ApplicationsRoth Nils0Martindale Christine F.1Eskofier Bjoern M.2Gaßner Heiko3Kohl Zacharias4Klucken Jochen5Machine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander-University Erlangen-Nürnberg (FAU),Erlangen, GermanyMachine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander-University Erlangen-Nürnberg (FAU),Erlangen, GermanyMachine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander-University Erlangen-Nürnberg (FAU),Erlangen, GermanyDepartment of Molecular Neurology, University Hospital,Erlangen, GermanyDepartment of Molecular Neurology, University Hospital,Erlangen, GermanyDepartment of Molecular Neurology, University Hospital,Erlangen, GermanyWearable sensor systems are of increasing interest in clinical gait analysis. However, little information about gait dynamics of patients under free living conditions is available, due to the challenges of integrating such systems unobtrusively into a patient’s everyday live. To address this limitation, new, fully integrated low power sensor insoles are proposed, to target applications particularly in home-monitoring scenarios. The insoles combine inertial as well as pressure sensors and feature wireless synchronization to acquire biomechanical data of both feet with a mean timing offset of 15.0 μs. The proposed system was evaluated on 15 patients with mild to severe gait disorders against the GAITRite® system as reference. Gait events based on the insoles’ pressure sensors were manually extracted to calculate temporal gait features such as double support time and double support. Compared to the reference system a mean error of 0.06 s ±0.06 s and 3.89 % ±2.61 % was achieved, respectively. The proposed insoles proved their ability to acquire synchronized gait parameters and address the requirements for home-monitoring scenarios, pushing the boundaries of clinical gait analysis.https://doi.org/10.1515/cdbme-2018-0103gaitinsolehome-monitoringsynchronizationdouble support |
| spellingShingle | Roth Nils Martindale Christine F. Eskofier Bjoern M. Gaßner Heiko Kohl Zacharias Klucken Jochen Synchronized Sensor Insoles for Clinical Gait Analysis in Home-Monitoring Applications Current Directions in Biomedical Engineering gait insole home-monitoring synchronization double support |
| title | Synchronized Sensor Insoles for Clinical Gait Analysis in Home-Monitoring Applications |
| title_full | Synchronized Sensor Insoles for Clinical Gait Analysis in Home-Monitoring Applications |
| title_fullStr | Synchronized Sensor Insoles for Clinical Gait Analysis in Home-Monitoring Applications |
| title_full_unstemmed | Synchronized Sensor Insoles for Clinical Gait Analysis in Home-Monitoring Applications |
| title_short | Synchronized Sensor Insoles for Clinical Gait Analysis in Home-Monitoring Applications |
| title_sort | synchronized sensor insoles for clinical gait analysis in home monitoring applications |
| topic | gait insole home-monitoring synchronization double support |
| url | https://doi.org/10.1515/cdbme-2018-0103 |
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