A Marker Based Optical Measurement Procedure to Analyse Robot Arm Movements and Its Application to Improve Accuracy of Industrial Robots

Rettig, Oliver; Müller, Silvan; Strand, Marcus

doi:10.1007/978-3-030-95892-3_42

Cited by 3 publications

(1 citation statement)

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“…x, y, and z represent a vector, and w is a scalar that stores the rotation around the vector. The most accurate data are obtained with Vero Vicon, with an error of 0.1 mm [ 59 ]. However, the error estimate is not defined for either glove.…”

Section: Resultsmentioning

confidence: 99%

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

Otero-González

Caeiro-Rodríguez

Rodríguez-D’Jesús

2022

Sensors

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Gastrointestinal endoscopy is a complex procedure requiring the mastery of several competencies and skills. This procedure is in increasing demand, but there exist important management and ethical issues regarding the training of new endoscopists. Nowadays, this requires the direct involvement of real patients and a high chance of the endoscopists themselves suffering from musculoskeletal conditions. Colonoscopy quantification can be useful for improving these two issues. This paper reviews the literature regarding efforts to quantify gastrointestinal procedures and focuses on the capture of hand and finger kinematics. Current technologies to support the capture of data from hand and finger movements are analyzed and tested, considering smart gloves and vision-based solutions. Manus VR Prime II and Stretch Sense MoCap reveal the 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 the main problem in gastrointestinal procedure scenarios: occlusion. In both cases, calibration and data interoperability are also key issues that limit possible applications. In conclusion, new advances are needed to quantify hand and finger kinematics in an appropriate way to support further developments.

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Section: Resultsmentioning

confidence: 99%