The effect of gaze position on lower limb joint angle and foot clearance during walking

2020 ◽  
Vol 2020 (0) ◽  
pp. A-7-1
Author(s):  
Ryouichi KURIHARA ◽  
Takeo MARUYAMA
Robotica ◽  
2019 ◽  
Vol 37 (12) ◽  
pp. 2014-2034 ◽  
Author(s):  
Christian Di Natali ◽  
Tommaso Poliero ◽  
Matteo Sposito ◽  
Eveline Graf ◽  
Christoph Bauer ◽  
...  

SummaryWearable devices are fast evolving to address mobility and autonomy needs of elderly people who would benefit from physical assistance. Recent developments in soft robotics provide important opportunities to develop soft exoskeletons (also called exosuits) to enable both physical assistance and improved usability and acceptance for users. The XoSoft EU project has developed a modular soft lower limb exoskeleton to assist people with low mobility impairments. In this paper, we present the design of a soft modular lower limb exoskeleton to improve person’s mobility, contributing to independence and enhancing quality of life. The novelty of this work is the integration of quasi-passive elements in a soft exoskeleton. The exoskeleton provides mechanical assistance for subjects with low mobility impairments reducing energy requirements between 10% and 20%. Investigation of different control strategies based on gait segmentation and actuation elements is presented. A first hip–knee unilateral prototype is described, developed, and its performance assessed on a post-stroke patient for straight walking. The study presents an analysis of the human–exoskeleton energy patterns by way of the task-based biological power generation. The resultant assistance, in terms of power, was 10.9% ± 2.2% for hip actuation and 9.3% ± 3.5% for knee actuation. The control strategy improved the gait and postural patterns by increasing joint angles and foot clearance at specific phases of the walking cycle.


Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6533
Author(s):  
Xinxin Li ◽  
Zuojun Liu ◽  
Xinzhi Gao ◽  
Jie Zhang

A novel method for recognizing the phases in bicycling of lower limb amputees using support vector machine (SVM) optimized by particle swarm optimization (PSO) is proposed in this paper. The method is essential for enhanced prosthetic knee joint control for lower limb amputees in carrying out bicycling activity. Some wireless wearable accelerometers and a knee joint angle sensor are installed in the prosthesis to obtain data on the knee joint and ankle joint horizontal, vertical acceleration signal and knee joint angle. In order to overcome the problem of high noise content in the collected data, a soft-hard threshold filter was used to remove the noise caused by the vibration. The filtered information is then used to extract the multi-dimensional feature vector for the training of SVM for performing bicycling phase recognition. The SVM is optimized by PSO to enhance its classification accuracy. The recognition accuracy of the PSO-SVM classification model on testing data is 93%, which is much higher than those of BP, SVM and PSO-BP classification models.


Work ◽  
2020 ◽  
Vol 65 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Seon-Chil Kim ◽  
Woon-Su Cho ◽  
Sung-Hyoun Cho

2012 ◽  
Vol 35 (2) ◽  
pp. 186-191 ◽  
Author(s):  
Kerstin L. Larsen ◽  
Grethe Maanum ◽  
Kathrine F. Frøslie ◽  
Reidun Jahnsen

Robotica ◽  
2017 ◽  
Vol 36 (3) ◽  
pp. 395-407 ◽  
Author(s):  
Nicholas B. Melo ◽  
Carlos E. T. Dórea ◽  
Pablo J. Alsina ◽  
Márcio V. Araújo

SUMMARYIn this work, we propose a method able to find user-oriented gait trajectories that can be used in powered lower limb orthosis applications. Most research related to active orthotic devices focuses on solving hardware issues. However, the problem of generating a set of joint trajectories that are user-oriented still persists. The proposed method uses principal component analysis to extract shared features from a gait dataset, taking into consideration gait-related variables such as joint angle information and the user's anthropometric features, used directly in an orthosis application. The trajectories of joint angles used by the model are represented by a given number of harmonics according to their respective Fourier series analyses. This representation allows better performance of the model, whose capability to generate gait information is validated through experiments using a real active orthotic device, analysing both joint motor energy consumption and user metabolic effort.


2017 ◽  
Vol 17 (07) ◽  
pp. 1740042
Author(s):  
YANG LIU ◽  
YONGSHENG GAO ◽  
YANHE ZHU

Wearable lower limb exoskeleton has comprehensive applications such as load-carrying augmentation, walking assistance, and rehabilitation training by using many active actuators in the joints to reduce the metabolic cost generally. The traditional fully actuated exoskeleton is bulky and requires large energy consumption, and the passive exoskeleton is difficult to provide effective power assistance. To achieve both small number of actuators and good assisting performance, this paper proposes a cable-pulley underactuated principle-based lower limb exoskeleton. The exoskeleton dynamics was modeled and the human-exoskeleton hybrid model was analyzed via ADAMS and LifeMOD to provide an evaluation method for power assistance. By exploiting the control strategy and utilizing the synergies of torque and power assistance, the hip joint and the knee joint can be actuated by a single cable simultaneously. Moreover, the human-exoskeleton co-simulation method was utilized to verify the assisting performance and control effect. In this simulation, the upper toque peak and power required by human are obviously reduced by power assistance and the joint angle curves without exoskeleton are in accordance with the joint angle curves with exoskeleton almost. In conclusion, the designed exoskeleton is compatible with human motion and feasible to provide effective power assistance in load-carrying walking.


2012 ◽  
Vol 24 (6) ◽  
pp. 471-474 ◽  
Author(s):  
Hyo-Taek Lee ◽  
Yong-Jae Kim ◽  
Hyo-lyun Roh
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document