A Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial Sensors
Segmentation of running data into gait cycles and stance/swing phases is crucial for evaluating running biomechanics. The benefit of magneto-inertial sensors is their ability to capture data in outdoor conditions. However, state-of-the-art inertial-based methods for estimating running temporal param...
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2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10843705/ |
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| author | Rachele Rossanigo Marco Caruso Elena Dipalma Cristine Agresta Lucia Ventura Franca Deriu Andrea Manca Taian M. Vieira Valentina Camomilla Andrea Cereatti |
| author_facet | Rachele Rossanigo Marco Caruso Elena Dipalma Cristine Agresta Lucia Ventura Franca Deriu Andrea Manca Taian M. Vieira Valentina Camomilla Andrea Cereatti |
| author_sort | Rachele Rossanigo |
| collection | DOAJ |
| description | Segmentation of running data into gait cycles and stance/swing phases is crucial for evaluating running biomechanics. The benefit of magneto-inertial sensors is their ability to capture data in outdoor conditions. However, state-of-the-art inertial-based methods for estimating running temporal parameters are limited to a restricted range of running speeds and, thus, not able to analyze running at variable speeds. This limitation prevents their use for real-world analysis for a wide range of runners and for sports disciplines where athletes vary their running speed. This study evaluated the speed-dependance of eight relevant foot-mounted inertial-based methods from previous research and proposed a novel method that could be robust to speed changes. The proposed method applied, for the first time, a template-matching algorithm based on dynamic time warping to running analysis and compared it to existing methods. All the implemented methods were tested on 30 runners at different speeds ranging from jogging to sprinting (8 km/h, 10 km/h, 14 km/h, 19-30 km/h) on both treadmill and overground. The most speed-robust performance was achieved by the proposed template-based method, providing estimation errors below 0.1% in stride, between 7%-19% in stance, and between 3%-6% in swing across running speeds. Conversely, all the tested methods from the literature were significantly speed-dependent. Thus, this study suggested that template-based approach is a valid solution for the inertial-based estimation of temporal parameters during running from slow jogging to fast sprinting. MATLAB codes and templates have been made available online. |
| format | Article |
| id | doaj-art-fbbbec86a17949aebf68b26ca372acd2 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| spelling | doaj-art-fbbbec86a17949aebf68b26ca372acd22025-01-28T00:01:33ZengIEEEIEEE Access2169-35362025-01-0113156041561710.1109/ACCESS.2025.353068710843705A Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial SensorsRachele Rossanigo0https://orcid.org/0009-0003-0805-5364Marco Caruso1https://orcid.org/0000-0002-1529-8095Elena Dipalma2Cristine Agresta3https://orcid.org/0000-0003-4861-6085Lucia Ventura4https://orcid.org/0000-0001-7302-743XFranca Deriu5Andrea Manca6Taian M. Vieira7https://orcid.org/0000-0002-6239-7301Valentina Camomilla8Andrea Cereatti9https://orcid.org/0000-0002-7276-5382Department of Biomedical Sciences, University of Sassari, Sassari, ItalyInteruniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, University of Rome “Foro Italico,”, Rome, ItalyDepartment of Electronics and Telecommunications, Politecnico di Torino, Turin, ItalyDepartment of Rehabilitation Medicine, University of Washington, Seattle, WA, USADepartment of Biomedical Sciences, University of Sassari, Sassari, ItalyDepartment of Biomedical Sciences, University of Sassari, Sassari, ItalyDepartment of Biomedical Sciences, University of Sassari, Sassari, ItalyDepartment of Electronics and Telecommunications, Politecnico di Torino, Turin, ItalyInteruniversity Centre of Bioengineering of the Human Neuromusculoskeletal System, University of Rome “Foro Italico,”, Rome, ItalyDepartment of Electronics and Telecommunications, Politecnico di Torino, Turin, ItalySegmentation of running data into gait cycles and stance/swing phases is crucial for evaluating running biomechanics. The benefit of magneto-inertial sensors is their ability to capture data in outdoor conditions. However, state-of-the-art inertial-based methods for estimating running temporal parameters are limited to a restricted range of running speeds and, thus, not able to analyze running at variable speeds. This limitation prevents their use for real-world analysis for a wide range of runners and for sports disciplines where athletes vary their running speed. This study evaluated the speed-dependance of eight relevant foot-mounted inertial-based methods from previous research and proposed a novel method that could be robust to speed changes. The proposed method applied, for the first time, a template-matching algorithm based on dynamic time warping to running analysis and compared it to existing methods. All the implemented methods were tested on 30 runners at different speeds ranging from jogging to sprinting (8 km/h, 10 km/h, 14 km/h, 19-30 km/h) on both treadmill and overground. The most speed-robust performance was achieved by the proposed template-based method, providing estimation errors below 0.1% in stride, between 7%-19% in stance, and between 3%-6% in swing across running speeds. Conversely, all the tested methods from the literature were significantly speed-dependent. Thus, this study suggested that template-based approach is a valid solution for the inertial-based estimation of temporal parameters during running from slow jogging to fast sprinting. MATLAB codes and templates have been made available online.https://ieeexplore.ieee.org/document/10843705/Contact timeinertial measurement unit (IMU)runningsprintingtemporal parameterswearable sensors |
| spellingShingle | Rachele Rossanigo Marco Caruso Elena Dipalma Cristine Agresta Lucia Ventura Franca Deriu Andrea Manca Taian M. Vieira Valentina Camomilla Andrea Cereatti A Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial Sensors IEEE Access Contact time inertial measurement unit (IMU) running sprinting temporal parameters wearable sensors |
| title | A Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial Sensors |
| title_full | A Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial Sensors |
| title_fullStr | A Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial Sensors |
| title_full_unstemmed | A Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial Sensors |
| title_short | A Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial Sensors |
| title_sort | speed invariant template based approach for estimating running temporal parameters using inertial sensors |
| topic | Contact time inertial measurement unit (IMU) running sprinting temporal parameters wearable sensors |
| url | https://ieeexplore.ieee.org/document/10843705/ |
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