Three dimensional motion capture applied to violin playing: A study on feasibility and characterization of the motor strategy

Ancillao, Andrea; Savastano, Bernardo; Galli, Manuela; Albertini, G.

doi:10.1016/j.cmpb.2017.07.005

Cited by 42 publications

(28 citation statements)

References 24 publications

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“…Meanwhile, there are many reports of CV measurement of the range of motion of finger and wrist previously. Most of these were about 0.05–0.06 using the gyroscope, optical motion capture, and goniometer [ 41 – 43 ], and almost all the results of our study were similar values.…”

Section: Discussionsupporting

confidence: 79%

A new method of measuring the thumb pronation and palmar abduction angles during opposition movement using a three-axis gyroscope

et al. 2018

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BackgroundThumb opposition is vital for hand function and involves pronation and palmar abduction. The improvement of pronation is often used as one of the evaluation items of the opponensplasty method for severe carpal tunnel syndrome. However, most of the studies used substitution evaluation methods for measurement of the pronation angle. Thus, there is still no appropriate method for measuring thumb pronation angle accurately in carpal tunnel syndrome patients.In recent reports, a wearable gyroscope was used to evaluate upper extremity motions and it can be possibly used for accurate measurement of the thumb pronation angle along the three-dimensionally moving bone axis.Thus, we investigated the reliability of measuring thumb pronation using a gyroscope and evaluated whether this method can be used to detect opposition impairment.MethodsThe participants were volunteers with unaffected upper limbs (32 hands) and patients with carpal tunnel syndrome (27 hands). The pronation and palmar abduction angles during opposition movements were measured using a three-axis gyroscope that included a three-axis accelerometer. The gyroscope was fixed onto the first metacarpal bone and the thumb phalanx.ResultsThe pronation and palmar abduction angles of the metacarpal bone and the palmar abduction angles of the phalanx significantly decreased in the carpal tunnel syndrome group. The pronation angle of the metacarpal bone during opposition movement peaked later than the palmar abduction angle in all hands.ConclusionsWe were able to measure the thumb pronation and palmar abduction angles using the three-axis gyroscope, and this tool was able to detect impairments of thumb opposition due to carpal tunnel syndrome. This could be a tool for measuring thumb and finger angles and for detecting impairments caused by various diseases.

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Section: Discussionsupporting

confidence: 79%

A new method of measuring the thumb pronation and palmar abduction angles during opposition movement using a three-axis gyroscope

et al. 2018

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“…Such systems can be easily integrated with other acquisition devices such as electromyography, video recording or force sensors, providing reliable sets of data for an integrated, multifactorial functional evaluation [ 1 ]. Such systems were successfully applied to gait analysis [ 6 ], jumping analysis [ 7 ], upper limb evaluation and other physical tasks [ 8 , 9 ]. When repeated cyclic trials are required, e.g., to record several steps in walking or running, an instrumented treadmill can be used in conjunction with the OS [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Indirect Measurement of Ground Reaction Forces and Moments by Means of Wearable Inertial Sensors: A Systematic Review

Ancillao

Tedesco

Barton

et al. 2018

Sensors

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In the last few years, estimating ground reaction forces by means of wearable sensors has come to be a challenging research topic paving the way to kinetic analysis and sport performance testing outside of labs. One possible approach involves estimating the ground reaction forces from kinematic data obtained by inertial measurement units (IMUs) worn by the subject. As estimating kinetic quantities from kinematic data is not an easy task, several models and protocols have been developed over the years. Non-wearable sensors, such as optoelectronic systems along with force platforms, remain the most accurate systems to record motion. In this review, we identified, selected and categorized the methodologies for estimating the ground reaction forces from IMUs as proposed across the years. Scopus, Google Scholar, IEEE Xplore, and PubMed databases were interrogated on the topic of Ground Reaction Forces estimation based on kinematic data obtained by IMUs. The identified papers were classified according to the methodology proposed: (i) methods based on direct modelling; (ii) methods based on machine learning. The methods based on direct modelling were further classified according to the task studied (walking, running, jumping, etc.). Finally, we comparatively examined the methods in order to identify the most reliable approaches for the implementation of a ground reaction force estimator based on IMU data.

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“…Based on different settings (e.g., the camera numbers and marker protocols), the accuracy of the marker-based system can be close to 0.1 mm and the sampling frequency can be as high as 1000 Hz [24]. This type of systems have been used for many studies such as measuring hand movements [25] and robotic motion monitoring [26].…”

Section: Introductionmentioning

confidence: 99%

Electronic Skin Wearable Sensors for Detecting Lumbar–Pelvic Movements

Zhang

Haghighi

Burstein

et al. 2020

Sensors

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Background: A nanomaterial-based electronic-skin (E-Skin) wearable sensor has been successfully used for detecting and measuring body movements such as finger movement and foot pressure. The ultrathin and highly sensitive characteristics of E-Skin sensor make it a suitable alternative for continuously out-of-hospital lumbar–pelvic movement (LPM) monitoring. Monitoring these movements can help medical experts better understand individuals’ low back pain experience. However, there is a lack of prior studies in this research area. Therefore, this paper explores the potential of E-Skin sensors to detect and measure the anatomical angles of lumbar–pelvic movements by building a linear relationship model to compare its performance to clinically validated inertial measurement unit (IMU)-based sensing system (ViMove). Methods: The paper first presents a review and classification of existing wireless sensing technologies for monitoring of body movements, and then it describes a series of experiments performed with E-Skin sensors for detecting five standard LPMs including flexion, extension, pelvic tilt, lateral flexion, and rotation, and measure their anatomical angles. The outputs of both E-Skin and ViMove sensors were recorded during each experiment and further analysed to build the comparative models to evaluate the performance of detecting and measuring LPMs. Results: E-Skin sensor outputs showed a persistently repeating pattern for each movement. Due to the ability to sense minor skin deformation by E-skin sensor, its reaction time in detecting lumbar–pelvic movement is quicker than ViMove by ~1 s. Conclusions: E-Skin sensors offer new capabilities for detecting and measuring lumbar–pelvic movements. They have lower cost compared to commercially available IMU-based systems and their non-invasive highly stretchable characteristic makes them more comfortable for long-term use. These features make them a suitable sensing technology for developing continuous, out-of-hospital real-time monitoring and management systems for individuals with low back pain.

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Three dimensional motion capture applied to violin playing: A study on feasibility and characterization of the motor strategy

Cited by 42 publications

References 24 publications

A new method of measuring the thumb pronation and palmar abduction angles during opposition movement using a three-axis gyroscope

A new method of measuring the thumb pronation and palmar abduction angles during opposition movement using a three-axis gyroscope

Indirect Measurement of Ground Reaction Forces and Moments by Means of Wearable Inertial Sensors: A Systematic Review

Electronic Skin Wearable Sensors for Detecting Lumbar–Pelvic Movements

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