Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer
Abstract This data descriptor presents a comprehensive and replicable dataset and method for calculating the cervical range of motion (CROM) utilizing quaternion-based orientation analysis from Delsys inertial measurement unit (IMU) sensors. This study was conducted with 14 participants and analyzed...
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| Format: | Article |
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Nature Portfolio
2025-01-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-024-04351-4 |
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| author | Lee Keidan Rawan Ibrahim Evyatar Ohayon Chaim G. Pick Ella Been |
| author_facet | Lee Keidan Rawan Ibrahim Evyatar Ohayon Chaim G. Pick Ella Been |
| author_sort | Lee Keidan |
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| description | Abstract This data descriptor presents a comprehensive and replicable dataset and method for calculating the cervical range of motion (CROM) utilizing quaternion-based orientation analysis from Delsys inertial measurement unit (IMU) sensors. This study was conducted with 14 participants and analyzed 504 cervical movements in the Sagittal, Frontal and Horizontal planes. Validated against a Universal Goniometer and tested for reliability and reproducibility. Analysis showed strong validity in the sagittal plane (R = 0.828 ± 0.051) and moderate in the frontal (R = 0.573 ± 0.138), with limitations in the horizontal plane (R = 0.353 ± 0.122). Reliability was high across all planes (Sagittal: ICC = 0.855 ± 0.065, Frontal: ICC = 0.855 ± 0.015, Horizontal: ICC = 0.945 ± 0.005). Our model for CROM measurements is a valuable tool aiding diagnosis, treatment planning, and monitoring of cervical spine conditions. This study presents an accessible analysis process for biomechanical assessments in cervical and spinal fields. The dataset herein serves as a benchmark for state-of-the-art machine learning models predicting head/neck position, analyzing smoothness of movements, measuring standard motion patterns, and calibrating drift based on movement comparisons. |
| format | Article |
| id | doaj-art-33033d7b7f18496d8690e5b98940b8d3 |
| institution | Kabale University |
| issn | 2052-4463 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
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| series | Scientific Data |
| spelling | doaj-art-33033d7b7f18496d8690e5b98940b8d32025-01-05T12:08:18ZengNature PortfolioScientific Data2052-44632025-01-011211910.1038/s41597-024-04351-4Multi-Planar Cervical Motion Dataset: IMU Measurements and GoniometerLee Keidan0Rawan Ibrahim1Evyatar Ohayon2Chaim G. Pick3Ella Been4Department of Anatomy and Anthropology, Faculty of Medical & Health Sciences, Tel- Aviv UniversitySylvan Adams Sports Institute, Tel Aviv UniversitySylvan Adams Sports Institute, Tel Aviv UniversityDepartment of Anatomy and Anthropology, Faculty of Medical & Health Sciences, Tel- Aviv UniversityDepartment of Anatomy and Anthropology, Faculty of Medical & Health Sciences, Tel- Aviv UniversityAbstract This data descriptor presents a comprehensive and replicable dataset and method for calculating the cervical range of motion (CROM) utilizing quaternion-based orientation analysis from Delsys inertial measurement unit (IMU) sensors. This study was conducted with 14 participants and analyzed 504 cervical movements in the Sagittal, Frontal and Horizontal planes. Validated against a Universal Goniometer and tested for reliability and reproducibility. Analysis showed strong validity in the sagittal plane (R = 0.828 ± 0.051) and moderate in the frontal (R = 0.573 ± 0.138), with limitations in the horizontal plane (R = 0.353 ± 0.122). Reliability was high across all planes (Sagittal: ICC = 0.855 ± 0.065, Frontal: ICC = 0.855 ± 0.015, Horizontal: ICC = 0.945 ± 0.005). Our model for CROM measurements is a valuable tool aiding diagnosis, treatment planning, and monitoring of cervical spine conditions. This study presents an accessible analysis process for biomechanical assessments in cervical and spinal fields. The dataset herein serves as a benchmark for state-of-the-art machine learning models predicting head/neck position, analyzing smoothness of movements, measuring standard motion patterns, and calibrating drift based on movement comparisons.https://doi.org/10.1038/s41597-024-04351-4 |
| spellingShingle | Lee Keidan Rawan Ibrahim Evyatar Ohayon Chaim G. Pick Ella Been Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer Scientific Data |
| title | Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer |
| title_full | Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer |
| title_fullStr | Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer |
| title_full_unstemmed | Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer |
| title_short | Multi-Planar Cervical Motion Dataset: IMU Measurements and Goniometer |
| title_sort | multi planar cervical motion dataset imu measurements and goniometer |
| url | https://doi.org/10.1038/s41597-024-04351-4 |
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