scholarly journals Geometric Design of a Passive Mechanical Knee for Lower Extremity Wearable Devices Based on Anthropomorphic Foot Task Geometry Scaling

2015 ◽  
Author(s):  
Shramana Ghosh ◽  
Nina Robson ◽  
J. M. McCarthy
Keyword(s):  
Wearable Devices ◽  
Heel Strike ◽  
Kinematic Synthesis ◽  
Leg Injuries ◽  
Recovery Treatment ◽  
Optical Motion ◽  
Efficient Alternative ◽  
Foot Clearance ◽  
Optical Motion Capture ◽  
Four Bar Linkage

The standard recovery treatment for ankle and lower leg injuries consists of using underarm crutches. Hands-free crutches have recently emerged as a more comfortable, natural and energy efficient alternative. However in the currently available devices such as the iWalk-Free (iWALKFree, Inc., USA) the lack of a knee joint results in abnormal motion pattern at the hip and pelvic joints to ensure foot clearance during the swing phase of the gait. To address this shortcoming, the paper describes the kinematic synthesis of a planar passive four-bar linkage that can be used as a mechanical knee in lower limb exoskeletons and other wearable devices. The knee design is based on anthropomorphic foot walking trajectory obtained from optical motion capture system. The task geometry at the foot, related to the contact and curvature constraints between the foot and the ground at two critical positions ‘heel strike’ and ‘toe off’ is scaled to the knee level. Velocity and acceleration specifications compatible with the contact and curvature constraints assist in defining the synthesis equations for the knee design. A working prototype of a passive wearable crutch substitute that incorporates the mechanical knee shows the applicability of the proposed technique.

scholarly journals Use of the Azure Kinect to measure foot clearance during obstacle crossing

2021 ◽  
Author(s):  
Kohei Yoshimoto ◽  
Masahiro Shinya
Keyword(s):  
Motion Capture ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Random Errors ◽  
Obstacle Crossing ◽  
Risk Of Falls ◽  
Optical Motion ◽  
Foot Clearance ◽  
Optical Motion Capture ◽  
Motion Capture Systems

Obstacle crossing is a typical adaptive locomotion known to be related to the risk of falls. Previous conventional studies have used elaborate and costly optical motion capture systems, which not only represent a considerable expense but also require participants to visit a laboratory. To overcome these shortcomings, we aimed to develop a practical and inexpensive solution for measuring obstacle-crossing behavior by using the Microsoft Azure Kinect, one of the most promising markerless motion capture systems. We validated the Azure Kinect as a tool to measure foot clearance and compared its performance to that of an optical motion capture system (Qualisys). We also determined the effect of the Kinect sensor placement on measurement performance. Sixteen healthy young men crossed obstacles of different heights (50, 150, and 250 mm). Kinect sensors were placed in front of and beside the obstacle as well as diagonally between those positions. As indices of measurement quality, we counted the number of measurement failures and calculated the systematic and random errors between the foot clearance measured by the Kinect and Qualisys. We also calculated the Pearson correlation coefficients between the Kinect and Qualisys measurements. The number of measurement failures and the systematic and random error were minimized when the Kinect was placed diagonally in front of the obstacle on the same side as the trail limb. The high correlation coefficient (r > 0.890) observed between the Kinect and Qualisys measurements suggests that the Azure Kinect has excellent potential for measuring foot clearance during obstacle-crossing tasks.

Design of Wearable Lower Leg Orthotic Based on Six-Bar Linkage

2017 ◽  
Author(s):  
Shramana Ghosh ◽  
Nina Robson ◽  
J. M. McCarthy
Keyword(s):  
Lower Leg ◽  
Wearable Device ◽  
Skeletal Structure ◽  
Dimensional Synthesis ◽  
Leg Injuries ◽  
Orthotic Device ◽  
Serial Chain ◽  
Compact Size ◽  
Optical Motion ◽  
Optical Motion Capture

The paper presents the design of a lower leg orthotic device based on dimensional synthesis of multi-loop six-bar linkages. The wearable device is comprised of a 2R serial chain, termed the backbone, sized according to the wearer’s limb anthropometric dimensions. The paper is a result of our current efforts in proposing a systematic process for the development of 3D printed customized assistive devices for patients with reduced limb mobility, based on anthropometric data and physiological task. To design the wearable device, the physiological task of the limb is obtained using an optical motion capture system and its dimensions are set such that it matched the lower leg kinematics as closely as possible. As a next step a six-bar linkage is synthesized and ensured that its motion is as close as possible to the physiological task. Next, the 2R backbone is replaced by the wearer’s limb to provide the skeletal structure for the multi-loop wearable device. During the final stage of the process the 2R backbone is relocated to parallel the human’s limb on one side, providing support and stability. The designed device can be secured to the thigh of the user to guide the lower leg without causing any discomfort and to ensure a natural physiological gait trajectory. This results in orthotic device for assisting people with lower leg injuries with compact size and better wearability.

Dimensional Synthesis of a Passive Eight-Bar Slider Exo-Limb for Grasping Tasks

2016 ◽  
Author(s):  
Guan Rong Tan ◽  
Nina Robson ◽  
Gim Song Soh
Keyword(s):  
Motion Capture ◽  
Index Finger ◽  
Synthesis Method ◽  
Wearable Devices ◽  
Least Square ◽  
Dimensional Synthesis ◽  
Infra Red ◽  
Optical Motion ◽  
3D Printed ◽  
Optical Motion Capture

This paper describes a dimensional synthesis method used in the design of a passively actuated finger exoskeleton that takes into account the user limb anthropometric dimensions and contact requirements for grasping objects. The paper is the first step in our current efforts on design of wearable devices that use a common slider at the hand to passively actuate each exo-finger. The finger exoskeleton is comprised of a 3R serial limb and is constrained to an eight-bar slider mechanism. To design the exo-limb, the pose of the index finger was captured using an optical motion capture and its dimensions were determined using a constrained least square optimization of its center of rotation. To facilitate the data capture, a 3D printed wearable Infra-red (IR) marker system was designed and placed on the finger’s phalanx. To illustrate the approach, an example of the design of an index exo-finger is described.

scholarly journals Motion Generation of Passive Slider Multiloop Wearable Hand Devices

2017 ◽  
Vol 9 (4) ◽  
Author(s):  
Guan Rong Tan ◽  
Nina Patarinsky Robson ◽  
Gim Song Soh
Keyword(s):  
Human Skin ◽  
Motion Capture ◽  
Synthesis Method ◽  
Middle Finger ◽  
Wearable Devices ◽  
Least Square ◽  
Dimensional Synthesis ◽  
Motion Generation ◽  
Optical Motion ◽  
Optical Motion Capture

This paper describes a dimensional synthesis method used in the design of a passive finger exoskeleton that takes into account the user limb anthropometric dimensions and contact requirements for grasping objects. The paper is the first step in our current efforts on the design of wearable devices that use a common slider at the hand to passively drive each exofinger. The finger exoskeleton is comprised of a 3R serial limb and is constrained to multiloop eight-bar slider mechanism using two RR constraints. To design the exolimb, the pose of the limb was captured using an optical motion capture and its dimensions were determined using a constrained least square optimization, which takes into account human skin movement. To illustrate the generality of our approach, an example of the design of an index and middle finger exolimb is described.

scholarly journals Real-time gait metric estimation for everyday gait training with wearable devices in people poststroke

2021 ◽  
Vol 2 ◽  
Author(s):  
Philipp Arens ◽  
Christopher Siviy ◽  
Jaehyun Bae ◽  
Dabin K. Choe ◽  
Nikos Karavas ◽  
...  
Keyword(s):  
Real Time ◽  
Daily Living ◽  
Stride Length ◽  
Inertial Sensors ◽  
Gait Training ◽  
The Body ◽  
Optical Motion ◽  
Foot Clearance ◽  
Optical Motion Capture ◽  
Induced Changes

Abstract Hemiparetic walking after stroke is typically slow, asymmetric, and inefficient, significantly impacting activities of daily living. Extensive research shows that functional, intensive, and task-specific gait training is instrumental for effective gait rehabilitation, characteristics that our group aims to encourage with soft robotic exosuits. However, standard clinical assessments may lack the precision and frequency to detect subtle changes in intervention efficacy during both conventional and exosuit-assisted gait training, potentially impeding targeted therapy regimes. In this paper, we use exosuit-integrated inertial sensors to reconstruct three clinically meaningful gait metrics related to circumduction, foot clearance, and stride length. Our method corrects sensor drift using instantaneous information from both sides of the body. This approach makes our method robust to irregular walking conditions poststroke as well as usable in real-time applications, such as real-time movement monitoring, exosuit assistance control, and biofeedback. We validate our algorithm in eight people poststroke in comparison to lab-based optical motion capture. Mean errors were below 0.2 cm (9.9%) for circumduction, −0.6 cm (−3.5%) for foot clearance, and 3.8 cm (3.6%) for stride length. A single-participant case study shows our technique’s promise in daily-living environments by detecting exosuit-induced changes in gait while walking in a busy outdoor plaza.

scholarly journals An Intelligent In-Shoe System for Gait Monitoring and Analysis with Optimized Sampling and Real-Time Visualization Capabilities

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2869
Author(s):  
Jiaen Wu ◽  
Kiran Kuruvithadam ◽  
Alessandro Schaer ◽  
Richie Stoneham ◽  
George Chatzipirpiridis ◽  
...  
Keyword(s):  
Real Time ◽  
Inertial Sensor ◽  
Neurological Diseases ◽  
Principal Component ◽  
Sampling Frequency ◽  
Powerful Analytical Tool ◽  
Optical Motion ◽  
Analysis System ◽  
Optical Motion Capture ◽  
Gait Monitoring

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on technologies for the assessment of gait characteristics, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigenanalysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.

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