A Low-Power, Single-Chip Electronic Skin Interface for Prosthetic Applications

Schmitz, Joseph A.; Sherman, Jonathan M.; Hansen, Sam; Murray, Samuel J.; Balkir, S.; Hoffman, Michael W.

doi:10.1109/iscas.2019.8702424

Cited by 4 publications

(2 citation statements)

References 23 publications

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“…Our solution provides more channels with respect to analogous state-of-the-art electronic systems to acquire and process data from piezoelectric tactile sensors for touch sensing with robotic hands. In particular, the interface electronics for the system on chip device for prosthetic applications presented in [73] offers 13 channels only, while the voltage-mode approach to read PVDF taxel outputs proposed in [49] only manages data from nine sensors.…”

Section: Methodsmentioning

confidence: 99%

Full-hand electrotactile feedback using electronic skin and matrix electrodes for high-bandwidth human–machine interfacing

Abbass

Došen

Seminara

et al. 2022

Phil. Trans. R. Soc. A.

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Tactile feedback is relevant in a broad range of human–machine interaction systems (e.g. teleoperation, virtual reality and prosthetics). The available tactile feedback interfaces comprise few sensing and stimulation units, which limits the amount of information conveyed to the user. The present study describes a novel technology that relies on distributed sensing and stimulation to convey comprehensive tactile feedback to the user of a robotic end effector. The system comprises six flexible sensing arrays (57 sensors) integrated on the fingers and palm of a robotic hand, embedded electronics (64 recording channels), a multichannel stimulator and seven flexible electrodes (64 stimulation pads) placed on the volar side of the subject’s hand. The system was tested in seven subjects asked to recognize contact positions and identify contact sliding on the electronic skin, using distributed anode configuration (DAC) and single dedicated anode configuration. The experiments demonstrated that DAC resulted in substantially better performance. Using DAC, the system successfully translated the contact patterns into electrotactile profiles that the subjects could recognize with satisfactory accuracy ( i . e . median { IQR } of 88.6 { 11 } % for static and 93.3 { 5 } % for dynamic patterns). The proposed system is an important step towards the development of a high-density human–machine interfacing between the user and a robotic hand. This article is part of the theme issue ‘Advanced neurotechnologies: translating innovation for health and well-being’.

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Section: Methodsmentioning

confidence: 99%

Full-hand electrotactile feedback using electronic skin and matrix electrodes for high-bandwidth human–machine interfacing

Abbass

Došen

Seminara

et al. 2022

Phil. Trans. R. Soc. A.

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“…Miniaturization of electronic components using MEMS technology drastically reduced size, weight and stiffness of all electronic components on board and has provided space to mount on-board signal conditioning and data processing units. Using this technology, tactile sensors have been fabricated by researchers in different shapes resulting in triangular- (Schmitz et al , 2019), comb-shaped (Mukai et al , 2008a) and hexagonal-shaped taxels (Mittendorfer and Cheng, 2012). These structures have uniaxial bending and conformable to large curvature structures such as robotic shoulders or cylindrical rods but still not suitable for small surfaces such as fingertips or catheter of a surgical robot.…”

Section: Review Of Shape Sensing Methods and Fiber Optics Based Shape Sensingmentioning

confidence: 99%

Recent trends and role of large area flexible electronics in shape sensing application – a review

Shaik

Rufus

2021

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Purpose This paper aims to review the shape sensing techniques using large area flexible electronics (LAFE). Shape perception of humanoid robots using tactile data is mainly focused. Design/methodology/approach Research papers on different shape sensing methodologies of objects with large area, published in the past 15 years, are reviewed with emphasis on contact-based shape sensors. Fiber optics based shape sensing methodology is discussed for comparison purpose. Findings LAFE-based shape sensors of humanoid robots incorporating advanced computational data handling techniques such as neural networks and machine learning (ML) algorithms are observed to give results with best resolution in 3D shape reconstruction. Research limitations/implications The literature review is limited to shape sensing application either two- or three-dimensional (3D) LAFE. Optical shape sensing is briefly discussed which is widely used for small area. Optical scanners provide the best 3D shape reconstruction in the noncontact-based shape sensing; here this paper focuses only on contact-based shape sensing. Practical implications Contact-based shape sensing using polymer nanocomposites is a very economical solution as compared to optical 3D scanners. Although optical 3D scanners can provide a high resolution and fast scan of the 3D shape of the object, they require line of sight and complex image reconstruction algorithms. Using LAFE larger objects can be scanned with ML and basic electronic circuitory, which reduces the price hugely. Social implications LAFE can be used as a wearable sensor to monitor critical biological parameters. They can be used to detect shape of large body parts and aid in designing prosthetic devices. Tactile sensing in humanoid robots is accomplished by electronic skin of the robot which is a prime example of human–machine interface at workplace. Originality/value This paper reviews a unique feature of LAFE in shape sensing of large area objects. It provides insights from mechanical, electrical, hardware and software perspective in the sensor design. The most suitable approach for large object shape sensing using LAFE is also suggested.

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