Sensing and Control for Prosthetic Hands in Clinical and Research Applications

Osborn, Luke; Iskarous, Mark M.; Thakor, Nitish V.

doi:10.1016/b978-0-12-814659-0.00022-9

Cited by 14 publications

(5 citation statements)

References 90 publications

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“…The skin-fat layer thickness effect on the EI value can be demonstrated based on the apparent resistance (AR) calculation (4).…”

Section: Methodology For Selecting Es Geometric Dimensions For Ei Myo...mentioning

confidence: 99%

“…The problems of developing an anthropomorphic [ 1 ] neuromuscular interface have been considered in many studies [ 2 , 3 , 4 ]. The key point in the neuromuscular interfaces’ development is the definition of methods and biophysical principles for obtaining information about the performed movement, which should allow the determination of not only its type but also to carry out a numerical assessment of the movement force-torque characteristics [ 1 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

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Determination of the Geometric Parameters of Electrode Systems for Electrical Impedance Myography: A Preliminary Study

Briko

Kapravchuk

Kobelev

et al. 2021

Sensors

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The electrical impedance myography method is widely used in solving bionic control problems and consists of assessing the change in the electrical impedance magnitude during muscle contraction in real time. However, the choice of electrode systems sizes is not always properly considered when using the electrical impedance myography method in the existing approaches, which is important in terms of electrical impedance signal expressiveness and reproducibility. The article is devoted to the determination of acceptable sizes for the electrode systems for electrical impedance myography using the Pareto optimality assessment method and the electrical impedance signals formation model of the forearm area, taking into account the change in the electrophysical and geometric parameters of the skin and fat layer and muscle groups when performing actions with a hand. Numerical finite element simulation using anthropometric models of the forearm obtained by volunteers’ MRI 3D reconstructions was performed to determine a sufficient degree of the forearm anatomical features detailing in terms of the measured electrical impedance. For the mathematical description of electrical impedance relationships, a forearm two-layer model, represented by the skin-fat layer and muscles, was reasonably chosen, which adequately describes the change in electrical impedance when performing hand actions. Using this model, for the first time, an approach that can be used to determine the acceptable sizes of electrode systems for different parts of the body individually was proposed.

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“…The skin-fat layer thickness effect on the EI value can be demonstrated based on the apparent resistance (AR) calculation (4).…”

Section: Methodology For Selecting Es Geometric Dimensions For Ei Myo...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Determination of the Geometric Parameters of Electrode Systems for Electrical Impedance Myography: A Preliminary Study

Briko

Kapravchuk

Kobelev

et al. 2021

Sensors

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“…WitMotion is a company that has designed an AHRS IMU sensor with Bluetooth capacity for utilization within various fields including both engineering and the movement sciences [WitMotion BLE 5.0]. When paired with multiple other AHRS IMU devices, this device can assess movement about a joint and its biomechanical interaction with other joints during exercise activity regarding human movement [24].…”

Section: Sensor Technologymentioning

confidence: 99%

A Novel Framework for Analysis of Lower Limb Movements: Integration of Augmented Reality and Sensor-based Systems

2022

Sports Injr Med

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In paper, an augmented reality device was coupled with motion sensor units to function as a system of cooperative technologies for usage within exercise science and neurorehabilitation. Specifically, in a subfield of exercise science called biomechanics, the assessment and analysis of movements are critical to the evaluation and prescription of improvements for physical function in both daily and sport-specific activities. Furthermore, the systematic combination of these technologies provided potential end-users with a modality to perform exercise within, and correlated feedback based upon the end-user's exercise performance. Data collection specific to biomechanics can provide both the end-user and their evaluators with critical feedback that can be used to modify movement efficiency, improve exercise capacity, and evaluate exercise performance. By coordinating both technologies and completing movement-based experiments, the systems were successfully integrated.

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“…This has resulted in a shift to using inertial measurement units (IMUs). These portable devices consist of a tri-axial accelerometer, gyroscope and magnetometer to measure acceleration, angular velocity and magnetic field strength, as opposed to segment and joint angular kinematics [ 19 , 20 ]. The conversion of acceleration and velocity data to segment and joint angular kinematics can occur with IMUs, but issues arise with the double-integration of data such as sensor drift and offset from the joints’ centres of rotation and the high reliance on sensor orientation accuracy to quantify joint angles, so the accuracy of this method is questionable [ 21 , 22 , 23 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Movement Variability in Cycling: An Exploratory Study

Winter

Bellenger

Grimshaw

et al. 2023

Sensors

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The purpose of this study was to determine the test-retest repeatability of Blue Trident inertial measurement units (IMUs) and VICON Nexus kinematic modelling in analysing the Lyapunov Exponent (LyE) during a maximal effort 4000 m cycling bout in different body segments/joints. An additional aim was to determine if changes in the LyE existed across a trial. Twelve novice cyclists completed four sessions of cycling; one was a familiarisation session to determine a bike fit and become better accustomed to the time trial position and pacing of a 4000 m effort. IMUs were attached to the head, thorax, pelvis and left and right shanks to analyse segment accelerations, respectively, and reflective markers were attached to the participant to analyse neck, thorax, pelvis, hip, knee and ankle segment/joint angular kinematics, respectively. Both the IMU and VICON Nexus test-retest repeatability ranged from poor to excellent at the different sites. In each session, the head and thorax IMU acceleration LyE increased across the bout, whilst pelvic and shank acceleration remained consistent. Differences across sessions were evident in VICON Nexus segment/joint angular kinematics, but no consistent trend existed. The improved reliability and the ability to identify a consistent trend in performance, combined with their improved portability and reduced cost, advocate for the use of IMUs in analysing movement variability in cycling. However, additional research is required to determine the applicability of analysing movement variability during cycling.

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Sensing and Control for Prosthetic Hands in Clinical and Research Applications

Cited by 14 publications

References 90 publications

Determination of the Geometric Parameters of Electrode Systems for Electrical Impedance Myography: A Preliminary Study

Determination of the Geometric Parameters of Electrode Systems for Electrical Impedance Myography: A Preliminary Study

A Novel Framework for Analysis of Lower Limb Movements: Integration of Augmented Reality and Sensor-based Systems

Analysis of Movement Variability in Cycling: An Exploratory Study

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