Surface Feature Recognition and Grasped Object Slip Prevention With a Liquid Metal Tactile Sensor for a Prosthetic Hand

Moaed, A.; AlSaidi, Mostapha; Lin, Maohua; Liddle, Genevieve M.; Mondal, Kunal; Engeberg, Erik D.

doi:10.1109/biorob49111.2020.9224294

Cited by 12 publications

(13 citation statements)

References 19 publications

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“…Likewise, surfaces S T2 , S T3 , and S T4 each had four copies of textures T2, T3, and T4 to respectively contact and slide across ( Figure S4 ). We hypothesized that the slip speeds and inter-ridge spacing (d, Figure 6 ) of the different textures would impact the power spectral distribution of the LMS signals [ 3 , 4 , 17 ]. The mechanism to detect the textures and speeds was to use the spectral components of the LMS signals to train machine learning algorithms to distinguish between the time-frequency signatures specific to each texture and speed [ 4 ].…”

Section: Methodsmentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

“…The authors thank K. Mondal, M. Al-Saidi, and G. Liddle for their assistance with the sensor fabrication in the early stages of this work [ 4 ].…”

Section: Acknowledgmentsmentioning

confidence: 99%

“…Commercially available prosthetic hands like the i-limb Ultra ( Figure 1 ), which has six degrees of freedom (DOF), and the BeBionic prosthetic hand that has five powered DOFs, demonstrate the trend of increasing prosthesis dexterity [ 2 ], yet these state of the art prosthetic limbs lack tactile sensation capabilities when interacting with the environment and manipulating objects. The absence of sensory feedback can lead to a frustrating problem when grasped objects are crushed or dropped since the amputee is not directly aware of the prosthetic fingertip forces after the afferent neural pathway is severed [ 3 , 4 ]. Human hand control strategies depend heavily on touch sensations for object manipulation [ 5 ]; however, people with upper limb amputation are missing tactile sensations.…”

Section: Introductionmentioning

confidence: 99%

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Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition

Moaed

Paul

Aravelli

et al. 2021

Sensors

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Multifunctional flexible tactile sensors could be useful to improve the control of prosthetic hands. To that end, highly stretchable liquid metal tactile sensors (LMS) were designed, manufactured via photolithography, and incorporated into the fingertips of a prosthetic hand. Three novel contributions were made with the LMS. First, individual fingertips were used to distinguish between different speeds of sliding contact with different surfaces. Second, differences in surface textures were reliably detected during sliding contact. Third, the capacity for hierarchical tactile sensor integration was demonstrated by using four LMS signals simultaneously to distinguish between ten complex multi-textured surfaces. Four different machine learning algorithms were compared for their successful classification capabilities: K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and neural network (NN). The time-frequency features of the LMSs were extracted to train and test the machine learning algorithms. The NN generally performed the best at the speed and texture detection with a single finger and had a 99.2 ± 0.8% accuracy to distinguish between ten different multi-textured surfaces using four LMSs from four fingers simultaneously. The capability for hierarchical multi-finger tactile sensation integration could be useful to provide a higher level of intelligence for artificial hands.

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Section: Methodsmentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

“…The authors thank K. Mondal, M. Al-Saidi, and G. Liddle for their assistance with the sensor fabrication in the early stages of this work [ 4 ].…”

Section: Acknowledgmentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition

Moaed

Paul

Aravelli

et al. 2021

Sensors

Self Cite

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“…Flexible tactile sensors are playing an essential role in intelligent robotics [1,2], smart prosthetics [3], human-machine interface [4,5], and Internet of Things (IoTs) [6]. Inspired by human skin, several types of wearable and implantable electronic devices have been widely used in health monitoring [7], such as the detection of electrocardiogram (ECG) signals [8], pulse vibration [9], and body temperature [10].…”

Section: Introductionmentioning

confidence: 99%

3D Printing of Liquid Metal Based Tactile Sensor for Simultaneously Sensing of Temperature and Forces

Wang

Jin

et al. 2021

International Journal of Smart and Nano Materials

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Tactile sensors have been used for haptic perception in intelligent robotics, smart prosthetics, and human-machine interface. The development of multifunctional tactile sensor remains a challenge and limit its application in flexible electronics and devices. We propose a liquid metal based tactile sensor for both temperature and force sensing which is made by 3D printing. The structural design and working principle of liquid metal based tactile sensor are firstly described. A digital light processing-based printing process is developed to print two kinds of photosensitive resins with different hardness, and used to fabricate the tactile sensor. A Wheatstone bridge circuit is designed for decoupling the temperature and forces from the measured output voltages. Characterization tests show that the tactile sensor has relatively high force sensing sensitivity of 0.29 N -1 , and temperature sensing sensitivities are 0.55% °C −1 at 20 ~ 50 °C and 0.21% °C −1 at 50 ~ 80 °C, respectively. Then, the fabricated tactile sensor is mounted onto hand finger to measure the contact force and temperature during grasping. Results show that the 3D printed tactile sensor has excellent flexibility and durability and can accurately measure the temperature and contact forces, which demonstrate its potential in robotic manipulation applications.

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A User-Friendly Packaging Solution for Silicon-Based Pressure Die to Develop Prosthetic Tactile Sensing

et al. 2021

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Surface Feature Recognition and Grasped Object Slip Prevention With a Liquid Metal Tactile Sensor for a Prosthetic Hand

Cited by 12 publications

References 19 publications

Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition

Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition

3D Printing of Liquid Metal Based Tactile Sensor for Simultaneously Sensing of Temperature and Forces

A User-Friendly Packaging Solution for Silicon-Based Pressure Die to Develop Prosthetic Tactile Sensing

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