A wearable inertial system to assess the cervical spine mobility: Comparison with an optoelectronic-based motion capture evaluation

Duc, Cyntia; Salvia, Patrick; Lubansu, Alphonse; Feipel, Véronique; Aminian, Kamiar

doi:10.1016/j.medengphy.2013.09.002

Cited by 50 publications

(46 citation statements)

References 37 publications

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“…It should be noted that the advantage of the Rift is to provide an affordable immersive VR environment for the gaming industry, and the provided customized algorithm to track the goggles movement is not necessarily optimized for monitoring cervical spine mobility. If a VR environment is not included in a study, one can use multiple inertial sensors and functional calibrations to derive a better accuracy for cervical spine measurement, as proposed by Duc et al (2014).…”

Section: Discussionmentioning

confidence: 99%

“…It was found that inertial sensors attached on body segments can provide an approximate assessment of upper and lower extremity kinematics (Cutti et al, 2008;Favre et al, 2006). Specifically, placing inertial sensors on clinically identifiable positions, such as one on the head and one on the trunk, can provide good estimates on cervical spine mobility (Duc et al, 2014;Theobald et al, 2012). A very recent study (Cuesta-Vargas and Williams, 2014) also placed inertial sensors on the head to facilitate cervical spine manipulation during physiotherapy.…”

Section: Introductionmentioning

confidence: 99%

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The accuracy of the Oculus Rift virtual reality head-mounted display during cervical spine mobility measurement

Chen

Lin

et al. 2015

Journal of Biomechanics

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An inertial sensor-embedded virtual reality (VR) head-mounted display, the Oculus Rift (the Rift), monitors head movement so the content displayed can be updated accordingly. While the Rift may have potential use in cervical spine biomechanics studies, its accuracy in terms of cervical spine mobility measurement has not yet been validated. In the current study, a VR environment was designed to guide participants to perform prescribed neck movements. The cervical spine kinematics was measured by both the Rift and a reference motion tracking system. Comparison of the kinematics data between the Rift and the tracking system indicated that the Rift can provide good estimates on full range of motion (from one side to the other side) during the performed task. Because of inertial sensor drifting, the unilateral range of motion (from one side to neutral posture) derived from the Rift is more erroneous. The root-mean-square errors over a 1-min task were within 10° for each rotation axis. The error analysis further indicated that the inertial sensor drifted approximately 6° at the beginning of a trial during the initialization. This needs to be addressed when using the Rift in order to more accurately measure cervical spine kinematics. It is suggested that the front cover of the Rift should be aligned against a vertical plane during its initialization.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The accuracy of the Oculus Rift virtual reality head-mounted display during cervical spine mobility measurement

Chen

Lin

et al. 2015

Journal of Biomechanics

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“…Several IMU systems have been observed to accurately estimate joint kinematics of the upper arm/shoulder (Zhou et al 2006, Zhou and Hu 2007, Cutti et al 2008, Zhou et al 2008, De Vries et al 2010, Zhou and Hu 2010, El-Gohary and McNames 2012, the cervical spine (Jasiewicz et al 2007, Theobald et al 2012, Duc et al 2014, the lower extremity (Favre et al 2008, Picerno et al 2008, Ferrari et al 2010, Fong and Chan 2010, the trunk (Lee et al 2003, Goodvin et al 2006, Giansanti et al 2007, Plamondon et al 2007, Roetenberg et al 2007, Kim and Nussbaum 2013, and the whole body (Brodie et al 2008) in comparison to laboratory-based human motion analysis techniques such as optical motion capture (OMC) (Cuesta-Vargas et al 2010). Despite their agreement with OMC systems in a laboratory setting, most studies examining the accuracy of IMU-based measurements have not sufficiently evaluated the repeatability of those measurements over a substantial time period, such as over the course of a full work shift (Mieritz et al 2012, Bergamini et al 2014.…”

Section: Introductionmentioning

confidence: 99%

Accuracy and repeatability of an inertial measurement unit system for field-based occupational studies

et al. 2015

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The accuracy and repeatability of an inertial measurement unit (IMU) system for directly measuring trunk angular displacement and upper arm elevation were evaluated over eight hours (i) in comparison to a gold standard, optical motion capture (OMC) system in a laboratory setting, and (ii) during a field-based assessment of dairy parlour work. Sample-to-sample root mean square differences between the IMU and OMC system ranged from 4.1° to 6.6° for the trunk and 7.2°-12.1° for the upper arm depending on the processing method. Estimates of mean angular displacement and angular displacement variation (difference between the 90th and 10th percentiles of angular displacement) were observed to change <4.5° on average in the laboratory and <1.5° on average in the field per eight hours of data collection. Results suggest the IMU system may serve as an acceptable instrument for directly measuring trunk and upper arm postures in field-based occupational exposure assessment studies with long sampling durations. Practitioner Summary: Few studies have evaluated inertial measurement unit (IMU) systems in the field or over long sampling durations. Results of this study indicate that the IMU system evaluated has reasonably good accuracy and repeatability for use in a field setting over a long sampling duration.

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“…Duc, et al [74] recently used a wearable inertial sensor system to measure head and thorax kinematics and assessed the cervical spine mobility from these measurements. The wearable system consisted of two inertial sensors, one on the forehead and the second on the thorax, which were linked to a lightweight data-logger worn at the waist.…”

Section: Head and Neck Injuriesmentioning

confidence: 99%

Recent Advances in Wearable Sensors for Health Monitoring

2015

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Wearable sensor technology continues to advance and provide significant opportunities for improving personalized healthcare. In recent years, advances in flexible electronics, smart materials and low-power computing and networking have reduced barriers to technology accessibility, integration and cost, unleashing the potential for ubiquitous monitoring. This paper discusses recent advances in wearable sensors and systems that monitor movement, physiology and environment, with a focus on applications for Parkinson's disease, stroke, and head and neck injuries.

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A wearable inertial system to assess the cervical spine mobility: Comparison with an optoelectronic-based motion capture evaluation

Cited by 50 publications

References 37 publications

The accuracy of the Oculus Rift virtual reality head-mounted display during cervical spine mobility measurement

The accuracy of the Oculus Rift virtual reality head-mounted display during cervical spine mobility measurement

Accuracy and repeatability of an inertial measurement unit system for field-based occupational studies

Recent Advances in Wearable Sensors for Health Monitoring

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