Instrumentation of the Prosthesis PrHand Based on Soft-Robotics: Angle sensor with Optical Fiber

Arco, Laura De; Pontes, María José; Segatto, Marcelo E. V.; Cifuentes, Carlos A.; Díaz, Camilo A. R.

doi:10.1364/laop.2022.tu1b.2

Cited by 3 publications

(2 citation statements)

References 4 publications

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“…The characterization of the first sensor (side polish) was described in previous works [ 47 , 48 , 49 ]. This sensor was already used to instrument the PrHand prosthesis, and it is used in this study for comparison purposes.…”

Section: Methodsmentioning

confidence: 99%

Soft-Sensor System for Grasp Type Recognition in Underactuated Hand Prostheses

Arco

Pontes

Segatto

et al. 2023

Sensors

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This paper presents the development of an intelligent soft-sensor system to add haptic perception to the underactuated hand prosthesis PrHand. Two sensors based on optical fiber were constructed, one for finger joint angles and the other for fingertips’ contact force. Three sensor fabrications were tested for the angle sensor by axially rotating the sensors in four positions. The configuration with the most similar response in the four rotations was chosen. The chosen sensors presented a polynomial response with R2 higher than 92%. The tactile force sensors tracked the force made over the objects. Almost all sensors presented a polynomial response with R2 higher than 94%. The system monitored the prosthesis activity by recognizing grasp types. Six machine learning algorithms were tested: linear regression, k-nearest neighbor, support vector machine, decision tree, k-means clustering, and hierarchical clustering. To validate the algorithms, a k-fold test was used with a k = 10, and the accuracy result for k-nearest neighbor was 98.5%, while that for decision tree was 93.3%, enabling the classification of the eight grip types.

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Section: Methodsmentioning

confidence: 99%

Soft-Sensor System for Grasp Type Recognition in Underactuated Hand Prostheses

Arco

Pontes

Segatto

et al. 2023

Sensors

Self Cite

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“…For the development of the sensor, a polymeric optical fiber (SH4001, Mitsubishi Chemical Co.) is used according to the proceeding described in [18]. The working principle is intensity variations, so the changes in the fiber curvature are measured as changes in the voltage.…”

Section: Angle Sensor and Benchmarkmentioning

confidence: 99%

Pressure and Angle Sensors with Optical Fiber for Instrumentation of the PrHand Hand Prosthesis

Arco

Pontes

Segatto

et al. 2022

J. Phys.: Conf. Ser.

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The principal cause of upper limb amputations is due to traumatism. The prosthesis is an assistive device to help in the activities of daily for the amputee person. However, one of the latest reports shows that in developing countries there are around 30 million people without assistive devices. This work presents the development of two kinds of sensors for the PrHand, an upper limb prosthesis based on compliant mechanism and soft-robotics. The sensors are made with polymeric optical fiber (POF), due to their flexibility and low cost, and the working principle is based on intensity variation. The angle sensors are used for monitoring the interphalangeal joint of the fingers, and for the assessment were made cycles of closing and opening each finger. On the other hand, the force sensors are located at the tip of three fingers to track the force made over the objects. Before encoring the sensors were evaluated making five cycles of compressing and decompressing each sensor. The results show a linear behavior between the angle and the voltage variation, one most remarkable angle sensor result was with a sensibility of 0.0357 V/° and an R2 of 99 % closing and 0.0483 V/° opening. In the case of the force sensor, a polynomial relation was found between the voltage changes and the pressure over the sensor; in some cases, the relation between voltage changes and pressure could be linear but that depends on the construction of the sensor. Regarding the obtained R2 of 99 %, its sensibility was 0.0361 V/N compression and 0.0368 V/N decompression. In conclusion, was successfully developed two kinds of sensors for the instrumentation of PrHand prosthesis. It is expected to use angle and sensor variables as input in algorithms of Machine Learning to improve the detection of objects. One aspect to improve is to control in a better way the sensor construction parameters due to the considerable influence over the sensor behavior.

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Experimental Demonstration of an Angle Laser Sensor Based on an Optical Thinned Microfiber Mach-Zehnder Interferometer

Salceda-Delgado,

Martinez-Rios,

Enriquez-Gomez

2024

IEEE Sensors J.

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Instrumentation of the Prosthesis PrHand Based on Soft-Robotics: Angle sensor with Optical Fiber

Abstract: The development of a fiber optic sensor based on intensity variation for angle measurement of the PIP joint in the hand prosthesis PrHand based on soft-robotics is presented and discussed its viability

Cited by 3 publications

References 4 publications

Soft-Sensor System for Grasp Type Recognition in Underactuated Hand Prostheses

Soft-Sensor System for Grasp Type Recognition in Underactuated Hand Prostheses

Pressure and Angle Sensors with Optical Fiber for Instrumentation of the PrHand Hand Prosthesis

Experimental Demonstration of an Angle Laser Sensor Based on an Optical Thinned Microfiber Mach-Zehnder Interferometer

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