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1.
Rev Prat ; 70(5): 542-547, 2020 May.
Artigo em Francês | MEDLINE | ID: mdl-33058645

RESUMO

Practice of sports in the general population. According to several surveys, it is estimated that 33 to 46% of French people never do sport or physical exercise, and this proportion tends to increase over the years. Men generally do more sport than women, and the frequency of participation tends to decrease with advancing age. The sport is mainly practiced outdoors, and the practice in commercial health and sport centers remains very minority (on average 5% of the participants). More than half of the people who exercise or play sport practice sport alone, without supervision, in total autonomy; however, this form of practice varies according to the type of sport. The most popular sport activities are walking and running, followed by fitness activities (fitness, resistance exercises, yoga, etc.). Women are particularly attracted to sports such as horse riding, tennis or gymnastics. The regularity of practice depends on the type of sport, and among people who report playing sports, 57% follow at least 2 sessions per week, for most of the year. For the general population, it is mainly the maintenance of health, the need for general wellbeing and relaxation that motivate people who do exercise or play sport, much more than the taste for competition and the need to perform.


Assuntos
Esportes , Animais , Terapia por Exercício , Feminino , Cavalos , Humanos , Masculino , Inquéritos e Questionários , Caminhada
2.
Zh Nevrol Psikhiatr Im S S Korsakova ; 120(8. Vyp. 2): 73-80, 2020.
Artigo em Russo | MEDLINE | ID: mdl-33016680

RESUMO

OBJECTIVE: To compare the efficacy of walking function recovery in patients in the early recovery period of ischemic stroke (IS) using an exoskeleton for the lower extremities and an active-passive pedal exercise bike. MATERIAL AND METHODS: An open randomized study of 47 patients in the early recovery period of IS was conducted. The rehabilitation course included exercises on an ExoAtlet exoskeleton in group 1 and exercises on a pedal simulator for active-passive training (5 days a week for 2 weeks) in group 2. Several tests were used to evaluate treatment results, including the Hauser walking index, the 10-meter walking test, the Berg balance scale, stabilometry, and biomechanics of walking. The complete training course was completed by 20 patients of group 1 and 21 of group 2. RESULTS: There was a significant increase in strength in paretic muscles, postural stability, functional level and walking speed in patients of both groups, but in patients of group 1, the dynamics of recovery was more pronounced (p<0.05). In group 1, there was a significant decrease in the level of disability and an increase in daily activity, which was higher compared to group 2. An analysis of the main indicators of the statokinesiogram showed the more pronounced positive shifts in patients of group 1, but significant differences were found only in the dynamics of the length and area of the curve in the test with eyes open. When studying the biomechanics of walking, it was found that the function of walking was changed: there was a significant decrease in the speed of movement by 2.2 times, the length of a double step by 1.6 times, and the pace of walking by 1.3 times compared to normal indicators. After the end of exercises, a significant increase in the length of the double step, speed and pace of walking as well as a decrease in the period of the locomotor cycle were found in group 1. CONCLUSION: The study revealed a positive impact of hardware rehabilitation on locomotion, both with the use of an exoskeleton and an active-passive pedal simulator. The use of an exoskeleton, have the advantages resulting in a significantly greater recovery of strength, stability, speed and symmetry of walking over the same period of training. A significant increase in postural stability in vertical position was revealed.


Assuntos
Exoesqueleto Energizado , Procedimentos Cirúrgicos Robóticos , Robótica , Reabilitação do Acidente Vascular Cerebral , Acidente Vascular Cerebral , Humanos , Caminhada
3.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 798-802, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018106

RESUMO

BACKGROUND: Parkinson's disease (PD) is a chronic condition that can be diagnosed and monitored by evaluating changes in the gait and arm movement parameters. In the gait movement, each cycle consists of two phases: stance and swing. Using gait analysis techniques, it is possible to get spatiotemporal variables derived from both phases. OBJECTIVE: In this paper, we compared two techniques: wavelet and peak detection. Previously, the wavelet technique was assessed for the gait phases detection, and peak detection was evaluated for arm swing analysis. These methods were evaluated using a low-cost RGB-D camera as data input source. This comparison could provide a unified and integrated method to analyze gait and arm swing signals. METHODS: Twenty-five PD patients and 25 age-matched, healthy subjects were included. Mann-Whitney U test was used to compare the continuous variables between groups. Hamming distances and Spearman rank correlation were used to evaluate the agreement between the signals and the spatiotemporal variables obtained by both methods. RESULTS: PD group showed significant reductions in speed (wavelet p = 0.001, peak detection p <0.001) and significantly greater swing (wavelet p = 0.003, peak detection p =0.005) and stance times (wavelet p = 0.003, peak detection p =0.004). Hamming distances showed small differences between the signals obtained by both methods (16 to 18 signal points). A very strong correlation (Spearman rho > 0.8, p <0.05) was found between the spatiotemporal variables obtained by each signal processing technique. CONCLUSION: Wavelet and peak detection techniques showed a high agreement in the signal obtained from gait data. The spatiotemporal variables obtained by both methods showed significant differences between the walking patterns of PD patients and healthy subjects. The peak detection technique can be used for integral motion analysis, providing the identification of the phases in the gait cycle, and arm swing parameters.Clinical Relevance- this establishes that peaks and wavelet techniques are comparable and may use it interchangeably to process signals from the gait of Parkinson's disease patients to support diagnosis and follow up made by a clinical expert.


Assuntos
Transtornos Neurológicos da Marcha , Doença de Parkinson , Marcha , Análise da Marcha , Humanos , Doença de Parkinson/diagnóstico , Caminhada
4.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 808-811, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018108

RESUMO

Frailty and falls are the main causes of morbidity and disability in elderly people. The Timed Up-and-Go (TUG) test has been proposed as an appropriate method for evaluating elderly individuals' risk of falling. To analyze the TUG's potential for falls prediction, we conducted a clinical study with participants aged ≥ 65 years, living in nursing homes. We harvested 138 TUG recordings with the information, if patients used a walking aid or not and developed a method to predict the use of walking aids using a Random Forest Classifier for ultrasonic based TUG test recordings. We achieved a high accuracy with an Area Under the Curve (AUC) of 96,9% using a 20% leave out evaluation strategy. Automated collection of structured data from TUG recordings - like the use of a walking aid - may help to improve fall risk tools in future.


Assuntos
Fragilidade , Caminhada , Acidentes por Quedas/prevenção & controle , Idoso , Humanos , Aprendizado de Máquina , Programas de Rastreamento
5.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 940-943, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018139

RESUMO

Motion artifact contamination may adversely affect the interpretation of biological signals. The development of algorithms to detect, identify, quantify, and mitigate motion artifact is typically performed using a ground truth signal contaminated with previously recorded motion artifact, or simulated motion artifact. The diversity of available motion artifact recordings is limited, and the rationales for existing models of motion artifact are poorly described. In this paper we developed an autoregressive (AR) model of motion artifact based on data collected from 6 subjects walking at slow, medium, and fast paces. The AR model was evaluated for its ability to generate diverse data that replicated the properties of the experimental data. The simulated motion artifact data was successful at learning key time domain and frequency domain properties, including the mean, variance, and power spectrum of the data, but was ineffective for imitating the morphology and probability distribution of the motion artifact data (kurtosis % error of 100.9-103.6%). More sophisticated models of motion artifact may be necessary to develop simulations of motion artifact.


Assuntos
Artefatos , Processamento de Sinais Assistido por Computador , Algoritmos , Movimento (Física) , Caminhada
6.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1002-1006, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018154

RESUMO

This research focuses on the gait phase recognition using different sEMG and EEG features. Seven healthy volunteers, 23-26 years old, were enrolled in this experiment. Seven phases of gait were divided by three-dimensional trajectory of lower limbs during treadmill walking and classified by Library for Support Vector Machines (LIBSVM). These gait phases include loading response, mid-stance, terminal Stance, pre-swing, initial swing, mid-swing, and terminal swing. Different sEMG and EEG features were assessed in this study. Gait phases of three kinds of walking speed were analyzed. Results showed that the slope sign change (SSC) and mean power frequency (MPF) of sEMG signals and SSC of EEG signals achieved higher accuracy of gait phase recognition than other features, and the accuracy are 95.58% (1.4 km/h), 97.63% (2.0 km/h) and 98.10% (2.6 km/h) respectively. Furthermore, the accuracy of gait phase recognition in the speed of 2.6 km/h is better than other walking speeds.


Assuntos
Marcha , Caminhada , Adulto , Eletroencefalografia , Voluntários Saudáveis , Humanos , Velocidade de Caminhada , Adulto Jovem
7.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2849-2852, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018600

RESUMO

Cognitive load may be an important outcome measure for the effectiveness of assistive devices such as prostheses and exoskeletons, but cognitive load is not adequately assessed in part due to the indirect physiological measures traditionally used for evaluation. Robust, direct measures are now available through mobile electroencephalography (EEG), but there are no standard protocols for measuring cognitive load during ambulatory and postural activities. Here we provide a proof-of-concept protocol for measuring cognitive load using an auditory oddball cognitive task to elicit P3 event-related potentials (ERP) during three tasks: sitting, standing, and walking on a treadmill. Our results show that this protocol successfully elicited P3 in each task, with as little as 5 minutes of data collection per task. We found a difference in P3 during sitting and walking after approximately 30 minutes of task completion, indicating that the cognitive load of walking was higher than that of sitting (p = .012).


Assuntos
Eletroencefalografia , Caminhada , Cognição , Potencial Evocado P300 , Teste de Esforço
8.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2986-2990, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018633

RESUMO

Brain-computer interface (BCI) can provide a way for the disabled to interact with the outside world. Steady-state visual evoked potential (SSVEP), which evokes potential through visual stimulation is one of important BCI paradigms. In laboratory environment, the classification accuracy of SSVEPs is excellent. However, in motion state, the accuracy will be greatly affected and reduce quite a lot. In this paper, in order to improve the classification accuracy of the SSVEP signals in the motion state, we collected SSVEP data of five targets at three speeds of 0km/h, 2.5km/h and 5km/h. A compare network based on convolutional neural network (CNN) was proposed to learn the relationship between EEG signal and the template corresponding to each stimulus frequency and classify. Compared with traditional methods (i.e., CCA, FBCCA and SVM) and state-of-the-art method (CNN) on the collected SSVEP datasets of 20 subjects, the method we proposed always performed best at different speeds. Therefore, these results validated the effectiveness of the method. In addition, compared with the speed of 0 km / h, the accuracy of the compare network at a high walking rate (5km/h) did not decrease much, and it could still maintain a good performance.


Assuntos
Interfaces Cérebro-Computador , Caminhada , Eletroencefalografia , Potenciais Evocados Visuais , Humanos , Redes Neurais de Computação
9.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3094-3097, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018659

RESUMO

Gait can reflect human biological status during walking, which can be used for disease detect, identity verification or robot control, etc. Traditionally, gait analysis only classifies a gait cycle into a few discrete stages. In this paper, human gait will be decoded continuously using surface electromography (sEMG). The angle of knee joint and ankle joint during walking at different speed will be estimated at the same time by the proposed scheme. Four time domain features combined together will be used for the task. Six estimation methods will be compared and the best performance reaches the RMSE of 6.64° for knee and 3.89° for ankle. The proposed method shows great potential for the gait tracking problem.


Assuntos
Marcha , Caminhada , Articulação do Tornozelo , Análise da Marcha , Humanos , Articulação do Joelho
10.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3110-3113, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018663

RESUMO

Continuous observation of muscle activity could provide a comprehensive picture of the loads experienced by muscles and joints during daily life. However, a major limitation to the practical application of this approach is the need to have surface electromyography (sEMG) sensors on all involved muscles. In this work, we model the synergistic relationship between muscles as a Gaussian process enabling the inference of unmeasured muscle excitations using a subset of measured data. Specifically, we developed a model for a single subject which uses sEMG data from four leg muscles to estimate the muscle excitation time-series of six other leg muscles during level walking at a self-selected speed. The proposed technique was able to accurately estimate the held-out muscle excitation time-series of the six muscles with correlation coefficients ranging from 0.74 to 0.87 and with mean absolute error less than 3%.


Assuntos
Músculo Esquelético , Caminhada , Eletromiografia , Distribuição Normal
11.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3138-3141, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018670

RESUMO

The design of effective rehabilitation protocols relies on the ability to accurately assess the physical condition and the rehabilitative needs of the patient. Monitoring muscle fatigue can increase the usability of rehabilitative and restorative devices as it helps avoiding premature tiring and injury of patients whose resistance is already compromised. In this study, we collected EMG and accelerometer data from one healthy subject during a 30-minute walk on treadmill to determine the variations of muscle activation, and gait acceleration patterns, which, however subtle, could be interpreted as early indicators of muscle fatigue. Results show an increasing Tibialis Anterior (TA) and decreasing Soleus (SOL) and Gastrocnemius (GASL, GASM) activation towards the end of the task as compared to the beginning, as well as increasing acceleration peaks during the middle swing phase. By following the approach outlined here we can assess the efficiency and reduction of metabolic cost achieved by an exoskeleton. Furthermore, muscle fatigue may be linked to the efficacy of gait rehabilitation, where decreased muscle fatigue across sessions possibly indicates longer retention of benefits after training and increased walking capacity. This methodology can be used to benchmark novel exoskeletons, monitor fatigue to avoid premature tiring of patients, and optimize rehabilitation therapies.


Assuntos
Fadiga Muscular , Caminhada , Aceleração , Eletromiografia , Marcha , Humanos
12.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3142-3145, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018671

RESUMO

Today's standard clinical practice to assess the walking ability of patients with neurological disorders during rehabilitation is based on simple gait tests such as the six-minute walking test (6MWT). Since the outcome of these tests is the average walking speed only, the aim of this work was to show that the application of movement sensors during a standardized walking test for the population of spinal cord injured (SCI) patients provides additional information on gait quality not directly described by the average speed. Hence, gait features that are related to quantitative and qualitative aspects of gait were extracted from the ankle sensor recordings of 29 SCI subjects and 19 healthy controls performing the 6MWT. The subjects were clustered into groups based on these gait features, and six gait features were selected to demonstrate the key differences between the clusters. The correlation of these features to the outcome of the 6MWT is discussed with their implications on gait quality.


Assuntos
Traumatismos da Medula Espinal , Dispositivos Eletrônicos Vestíveis , Marcha , Humanos , Traumatismos da Medula Espinal/diagnóstico , Caminhada
13.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3150-3153, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018673

RESUMO

The purpose of this study is to investigate the effect of changing the application points and directions of the soft actuator band of a wearable hip assist device on muscle force and joint kinematics during gait. Healthy adult participants walked under four conditions with varying band positions of a soft wearable hip assist device. The three-dimensional coordinates of markers and ground reaction force data were measured during gait. Lower limb muscle forces and joint angles were calculated using a musculoskeletal model. Our results showed that the position and running direction of the soft actuator band decreased the forces of the iliopsoas and hamstring muscles.


Assuntos
Marcha , Dispositivos Eletrônicos Vestíveis , Adulto , Fenômenos Biomecânicos , Humanos , Extremidade Inferior , Caminhada
14.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3158-3161, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018675

RESUMO

Surface electromyography (sEMG) of the lower limb muscles has been proposed to evaluate motor dysfunctions in Parkinson's disease (PD) patients. Variability in the sEMG could be used as an indicator of poor muscle coordination, but previous studies have reported conflicting results. This study has examined the variability of muscle using the coefficients of variance of Tibialis anterior (TA) and Medial gastrocnemius (MG) lower limb muscles for 24 PD, 24 age matched controls (CO), and 24 young controls (YC), during different phases of the gait cycle. The gait intervals were measured using the inertial measurement unit (IMU). We observed a statistically significant difference between PD and control for the variability of lower limb muscle when comparing the sub-phases of the gait. It was also found that the difference was more pronounced for the TA muscle.


Assuntos
Doença de Parkinson , Caminhada , Eletromiografia , Marcha , Humanos , Músculo Esquelético
15.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3162-3165, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018676

RESUMO

Immersive virtual reality provides a safe and costeffective approach to administrating balance disruption during ambulation. Previous research has explored the effects of applying continuous perturbations in a virtual environment to challenge balance. This pilot study investigates the ability to disrupt balance with discrete visual perturbations during ambulation in healthy young adults. During the study participants walked on a treadmill within a virtual environment. As they walked the entire visual scene was intermittently shifted to the left or right 1 meter over 1 second. The results demonstrate a significant decrease in step length (p <; 0.05) and change in center of mass excursion (p <; 0.05) across participants (N=13). Changes in gait lasted up to three steps after application, suggesting a consistent challenge to dynamic balance control as a result of the discrete visual perturbation . Further, participants did not demonstrate a reduction in response to the discrete visual perturbation with repeated exposure. The results indicate that discrete visual perturbations of a virtual scene can be used to challenge gait and modulate center of mass sway. The use of visual perturbations within a virtual environment to challenge dynamic balance could provide a safer and more affordable avenue for balance rehabilitation by reducing the need for systems that physically perturb balance.


Assuntos
Marcha , Realidade Virtual , Teste de Esforço , Humanos , Projetos Piloto , Caminhada , Adulto Jovem
16.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3178-3183, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018680

RESUMO

With the aging population and rising rates of mobility disability, the demand for advanced smart rollators is increasing. To design control systems which improve safety and reliability, accurate prediction of human intent is required. In this paper, we present a classification method to predict intent of the rollator user using indirect inputs. The proposed classification algorithm uses data collected from an inertial measurement unit and an encoder implemented into a rollator. The developed intent estimation method is experimentally verified on our modified robotic platform. For our experiment with 7 healthy young adults, KNN classification algorithm was able to predict 3 intents (turn left, turn right and walk straight) with 92.9 % accuracy.


Assuntos
Intenção , Andadores , Idoso , Humanos , Aprendizagem , Reprodutibilidade dos Testes , Caminhada , Adulto Jovem
17.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3224-3227, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018691

RESUMO

Traumatic brain injury (TBI), is one of the leading causes of motor deficits in children and adults, affecting motor control, coordination, and acuity. This results in reduced functional ambulation and quality of life. Robotic exoskeletons (REs) are quickly becoming an effective method for gait neurorehabilitation in individuals with TBI. Neurorehabilitation is based on the principle that the human brain is capable of reorganization due to high dose motor training. Understanding the underlying mechanisms of cortical reorganization will help improve current rehabilitation. The objective of the study is to understand the cortical activity differences due to RE training and recovery of functional ambulation for individuals with chronic TBI, using functional near-infrared spectroscopy. There was an increase in cortical activation in the prefrontal cortex (PFC), bilateral premotor cortex (PMC) and motor cortex (M1) while walking with RE versus without RE at follow-up. Furthermore, decreased activation was observed in PFC, bilateral PMC and M1 from baseline to follow-up while walking without RE with a corresponding improvement in functional ambulation. These preliminary results for one participant provide initial evidence to understand the cortical mechanisms during RE gait training and the recovery induced due to the training.


Assuntos
Lesões Encefálicas Traumáticas , Procedimentos Cirúrgicos Robóticos , Adulto , Criança , Marcha , Humanos , Qualidade de Vida , Caminhada
18.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 3688-3691, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018801

RESUMO

Gait motion patterns such as step length, flexed posture, absent arm swing and bradykinesia, constitute the main source of information to describe and quantify Parkinson disease. Nevertheless, such quantification is commonly developed under marker based protocols, losing natural motion gestures, and only taking into account a limited description of the locomotion process. This work introduces a 3D convolutional gait representation, that uses markerless video sequences to automatically predict parkinsonian behaviours. A remarkable contribution herein presented is the quantification of spatio-temporal salient maps, that stand out body regions related with Parkinson disease, and result from activations that mainly contribute on the classification task. For doing so, a convolutional architecture is trained from a set of walking videos, recorded from parkinsonian and control subjects. Then, a prediction of disease is obtained according to motion patterns computed by convolutional learned scheme. Salience motion patterns are obtained by retro-propagating the output softmax network prediction over the video space. From a total of 22 patients, and a total of 176 video sequences, the proposed approach achieved an average accuracy score of 88%. Interestingly enough, the recovered salience maps focus the attention on relevant parkinsonian biomarkers such as the head motion and trunk posture, that namely is excluded on classical gait analysis.Clinical relevance- Salient spatio-temporal regions can potentially support and complement the diagnosis and the following of Parkinson's disease. Also, such complex relationships could potentially evolve in further understanding of this pathology.


Assuntos
Doença de Parkinson , Caminhada , Marcha , Análise da Marcha , Humanos , Movimento (Física)
19.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 4229-4232, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018930

RESUMO

Gait is an essential function for humans, and gait patterns in daily life provide meaningful information about a person's cognitive and physical health conditions. Inertial measurement units (IMUs) have emerged as a promising tool for low-cost, unobtrusive gait analysis. However, large varieties of IMU gait analysis algorithms and the lack of consensus for their validation make it difficult for researchers to assess the reliability of the algorithms for specific use cases. In daily life, individuals adapt their gait patterns in response to changes in the environment, making it necessary for IMU gait analysis algorithms to provide accurate measurements despite these gait variations. In this paper, we reviewed common types of IMU gait analysis algorithms and appropriate analysis methods to evaluate the accuracy of gait parameters extracted from IMU measurements. We then evaluated stride lengths and stride times calculated from a comprehensive double integration based IMU gait analysis algorithm using an optoelectric walkway as gold standard. In total, 729 strides from five healthy subjects and three different walking patterns were analyzed. Correlation analyses and Bland-Altman plots showed that this method is accurate and robust against large variations in walking patterns (stride length: correlation coefficient (r) was 0.99, root mean square error (RMSE) was 3% and average limits of agreement (LoA) was 6%; stride time: r was 0.95, RMSE was 4% and average LoA was 7%), making it suitable for gait evaluation in daily life situations. Due to the small sample size, our preliminary findings should be verified in future studies.


Assuntos
Algoritmos , Análise da Marcha , Marcha , Humanos , Reprodutibilidade dos Testes , Caminhada
20.
Stud Health Technol Inform ; 273: 91-96, 2020 Sep 04.
Artigo em Inglês | MEDLINE | ID: mdl-33087596

RESUMO

A lower-extremity exoskeleton can facilitate the lower limbs' rehabilitation by providing additional structural support and strength. This article discusses the design and implementation of a functional prototype of lower extremity brace actuation and its wireless communication control system. The design provides supportive torque and increases the range of motion after complications reducing muscular strength. The control system prototype facilitates elevating a leg, gradually followed by standing and slow walking. The main control modalities are based on an Artificial Neural Network (ANN). The prototype's functionality was tested by time-angle graphs. The final prototype demonstrates the potential application of the ANN in the control system of exoskeletons for joint impairment therapy.


Assuntos
Exoesqueleto Energizado , Extremidade Inferior , Redes Neurais de Computação , Torque , Caminhada
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