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Contributions to the quantification of manual skills with immersive devices

June 2022

Affiliation: University of Vigo

Authors:

Iván Otero González

University of Vigo

This year I have had the opportunity to learn more about the capabilities of the smart gloves and I have put them into practice by measuring movements that are part of the colonoscopy procedure. Furthermore I experimented with the Xsens, which allows motion body capture as a complement to identify the specialist's postures. And I have also recorded high precision movements with the Vero Vicon camera, which is key to my case study of recording manual motor skills. And thanks to direct contact with doctors from the public hospitals of Cunqueiro and Meixoeiro, I have been able to establish a unified protocol of measurement movements. Particularly, this is because they have hands with very different features, for example the great difference between men and women. And at the same time I am working with data extracted from these devices in order to obtain conclusions and patterns of good and bad movements.

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Iván Otero González

Contributions to the quantiﬁcation of

manual skills with immersive devices

Xsens

Smart Gloves

Vero Vicon

Medical-Colonoscopy

Safety - Firemen

Industry - Maintenance

Wind-turbine - Field work

Sectors Resources Contributions

Movement-measurement

Educational Resources

Training Environment

Data Analytics

Participants

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ResearchGate has not been able to resolve any references for this publication.

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Methods for Gastrointestinal Endoscopy Quantification: A Focus on Hands and Fingers Kinematics

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Gastrointestinal endoscopy is a complex procedure requiring the mastery of several competences and skills. This procedure is being increasingly demanded, but there exist important management and ethical issues regarding the training of new endoscopists. Nowadays, this requires direct involvement of real patients and the high chances to suffer musculoskeletal conditions by endoscopists themselves. ... [Show full abstract] This paper reviews the literature regarding efforts to quantify gastrointestinal procedures and focus on the capture of hand and finger kinematics. A solution towards these problems can come from quantification: measure to improve. Current technologies to support the capture of data from hands and fingers’ movements are analyzed and tested, considering smart-gloves and vision-based solutions. Manus VR Prime II and Stretch Sense MoCap reveal main problems with smart gloves related to the adaptation of the gloves to different hand sizes and comfortability. Regarding vision-based solutions, Vero Vicon cameras show a main problem in the gastrointestinal procedure scenario: occlusion. In both cases, calibration and data interoperability are also key issues that limit possible applications. As a conclusion, new advances are needed to quantify hands and finger kinematics in an appropriate way to support further developments.

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Management of VR/MR/AR technology for training in manual skills. Sectors like: - Medical-Colonoscopy...

July 2020

Iván Otero González

My name is Iván and the title of my research is Management of VR/MR/AR technology for training in manual skills. The sector in this case is the medical sector and as you can see focus on Colonoscopy. The resources are mainly the gloves but I also will use 360º camera in combination with headset 3D. And in terms of constributions I am totally sure there will be a lot of them but in this case, we ... [Show full abstract] want to measure the movements. The movements of hands and theirs fingers. Furthermore I will focus on the creation of a training environment as a repository of educational resources with the important proposal of giving learners of this medical procedures some guide lines that helps then to avoid typical injures. Well, I am sure you will need to know more about my work, so I invite you to make me more questions in the poster session. Thank you!! Here you are the video. Just with 1 minuto is enough. https://youtu.be/lhwyGKSCy8s

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Quantitative evaluation of subjective posture recognition by physiotherapists using a 3D motion capt...

August 2020 · Journal of Physical Therapy Science

[Purpose] This study evaluated subjective posture recognition by physiotherapists with expertise in posture, examined the quantification of posture using a three-dimensional (3D) motion capture, and described posture-based characteristics. [Participants and Methods] We photographed good, normal, and bad postures in 12 participants using an infrared camera, and the resultant data were analyzed. ... [Show full abstract] [Results] We observed the largest displacement from a good to a bad posture in the tenth thoracic vertebra on the X-axis in the anterior–posterior direction in comparison with other index points. Further, we observed considerable differences between good and bad postures compared with other index points. Moreover, we noted significant differences between the amount of displacement between good to a normal posture and from a good to a bad posture. The vertical displacement of the Z-axis was smaller than other index points. [Conclusion] Th10 captured features from the three postures. The X-axis was displaced most between good and bad postures. Further, the amount of displacement on the Z-axis was less between good and bad posture, rendering it difficult to capture features. Therefore, the findings reported herein can be used to compare the front and rear directions of the X-axis for capturing postural changes.

Last Updated: 01 Oct 2023