Nicholas Hale

A preliminary study on characterisation of finger interface kinetics using a pressure and shear sensor system

Background: Our hands constantly handle objects throughout our lives, where a crucial component of this interaction is the detection of grasping (pressure) and slipping (shear) of the object. While there have been a large amount of studies using pressure sensors for grasping detection, synchronised pressure and shear detection at the finger/object interface is still needed. Objectives: This study aims to assess the feasibility of a sensor system designed to detect both pressure and shear at the fingertip/object interface via a single subject test. Study design: Descriptive study, proof of concept. Methods: One healthy subject participated in the study and was asked to perform a single finger test protocol and a simple hand test protocol. The corresponding multidirectional loads at the fingertip/object interface were measured in real time using a pressure and shear sensor system. Results: Results from the finger test protocol show peak values of up to approximately 50 kPa (5 N) and 30 kPa (3 N) of pressure for each test, respectively. Results from the hand test protocol show a pressure and shear profile that shows a large increase in grip force during the initial grasping of the object, with a peak pressure of approximately 50 kPa (5 N). The pressure and shear profile demonstrates that the load is not evenly distributed across all digits. Conclusion: This study provides evidence that the reported sensor system has sufficient resolution, dynamic response and load capability to capture biomechanical information during basic protocols and hand-grasping tasks. Clinical relevance The presented sensor system could be potentially used as a tool for measuring and evaluating hand function and could be incorporated into a prosthetic hand as a tactile feedback system.

A comprehensive mechanotransduction model for tactile feedback based on multi-axial stresses at the fingertip-contact interface

This paper presents a mechanotransduction model designed to convert the multi-axial mechanical loads at the fingertip-contact interface into neural-spike trains, the MultiAxial Stress Mechanotransduction (MASM) model. Seeking a comprehensive solution and more direct integration with sensor systems in tactile applications, the model accounts for the conversion of multi-axial (pressure and shear) stresses at the fingertip-contact interface into spike trains with artificial slow adapting (SA) and rapidly adapting (RA) afferents type I (SAI, RAI) and II (SAII, RAII). These have been modelled based on the properties of those in human fingertips. To illustrate how the model works, artificial data mimicking typical stress stimuli profiles used to evaluate the response of biological afferents were fed to the model and results examined. Subsequently, the suitability of the model for real tactile applications was preliminary tested by inputting to the model real life, measured pressure and shear data in a fingertip ‘press-push-lift’ action. The response of the modelled afferents was analyzed and qualitatively compared to typical responses of biological units. Initial results show that it is possible to codify the mechanical contact tactile information measured by multi-axial sensor systems in a bio-inspired fashion, reproducing relevant features similar to those produced by biological mechanoreceptors.

Dataset for An Interfacial Pressure and Shear Sensor System for Fingertip Contact Applications

Dataset supporting: Valero, Maria et al (2016) An interfacial pressure and shear sensor system for fingertip contact applications. Healthcare Technology Letters.

Assessing trans-femoral residuum/socket interface coupling using 3D motion capture – effect of terrains and walking speeds

The aim of this study was to develop a new means to assess residuum/socket interface couplings at different speeds and walking over different terrains using motion capture methods and a conventional 6 degrees of freedom (6DoF) marker model.This dataset accompanies the following paper: Tang, Jing, Mcgrath, Michael, Hale, Nicholas, Jiang, Liudi, Bader, Dan, Moser, David, Laszczak, Piotr, Bradbury, Richard and Zahhedi, Saeed (2016) Assessing trans-femoral residuum/socket interface coupling using 3D motion capture – effect of terrains and walking speeds. Gait & Posture