Design and Control of an Assistive Bionic Joint for Leg Muscle Rehabilitation

2017 ◽  
Author(s):  
Vincent Nagel ◽  
Sarah Chu ◽  
Jack Forney ◽  
Lyle Kosinski ◽  
Vimal Viswanathan
Keyword(s):  
Response Time ◽  
Sensor Data ◽  
Full Extension ◽  
Rehabilitation Process ◽  
Leg Muscles ◽  
Finite Control ◽  
Recovery Times ◽  
Sensor Signals ◽  
Leg Muscle ◽  
And Control

This project aims to create an electronically powered and controlled knee brace to aid stroke victims with partial paralysis with their leg muscle rehabilitation process. The newly designed assistive bionic joint takes the functionality of the existing assistive knee braces to the next level by incorporating a control algorithm that uses sensor signals gathered from the patient’s leg muscles. Electromyography (EMG) is used for gathering impulse signals from electrodes placed on key muscles as inputs for the device. The action of each major leg muscle is replicated using a set of fluidic muscles that mimic the functionality of the actual leg muscles. A microcontroller is used to interpret sensor data and adjust the contraction length of the muscles, thereby providing the wearer with augmented strength and mobility. Initial testing of a proof-of-concept prototype has led to finite control over muscle contraction length based on sensor data and has a response time of 280ms from full extension to contraction. Further testing of the brace assembly, fluidic muscles and control system is conducted and the results indicate a 600ms response time due to a step input. This personalized, powered brace has many implications for the enrichment of muscle rehabilitation such as higher patient morale, more muscle activity, and shortened recovery times.

scholarly journals Development of a Virtual Reality Simulator for an Intelligent Robotic System Used in Ankle Rehabilitation

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1537
Author(s):  
Florin Covaciu ◽  
Adrian Pisla ◽  
Anca-Elena Iordan
Keyword(s):  
Virtual Reality ◽  
Muscle Activity ◽  
Human Subject ◽  
Robotic System ◽  
Virtual Reality Simulator ◽  
Robotic Rehabilitation ◽  
Rehabilitation Process ◽  
Leg Muscles ◽  
Ankle Rehabilitation ◽  
And Control

The traditional systems used in the physiotherapy rehabilitation process are evolving towards more advanced systems that use virtual reality (VR) environments so that the patient in the rehabilitation process can perform various exercises in an interactive way, thus improving the patient’s motivation and reducing the therapist’s work. The paper presents a VR simulator for an intelligent robotic system of physiotherapeutic rehabilitation of the ankle of a person who has had a stroke. This simulator can interact with a real human subject by attaching a sensor that contains a gyroscope and accelerometer to identify the position and acceleration of foot movement on three axes. An electromyography (EMG) sensor is also attached to the patient’s leg muscles to measure muscle activity because a patient who is in a worse condition has weaker muscle activity. The data collected from the sensors are taken by an intelligent module that uses machine learning to create new levels of exercise and control of the robotic rehabilitation structure of the virtual environment. Starting from these objectives, the virtual reality simulator created will have a low dependence on the therapist, this being the main improvement over other simulators already created for this purpose.

scholarly journals Skeletal muscle and liver protein degradation in mice divergently selected for low and high body weight over 108 generations

2005 ◽  
Vol 48 (5) ◽  
pp. 505-517 ◽  
Author(s):  
S. J. Rosochacki ◽  
E. Wirth-Dzięciołowska ◽  
M. Zimowska ◽  
T. Sakowski ◽  
J. Połoszynowicz ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Body Weight ◽  
Cell Size ◽  
Cathepsin D ◽  
Liver Protein ◽  
Protein Catabolism ◽  
Leg Muscles ◽  
Leg Muscle ◽  
And Control ◽  
Old Mice

Abstract. Experiment was carried out on 111 and 13-14 weeks old mice divergently selected for low (L) and high (C) body weight over 108 generations. In leg muscle and liver cathepsin D (CatD) was determined as pepstatin sensitive activity (PSCatD), and as pepstatin-insensitive (PIA) and leupeptin-insensitive (LIA) acid autolytic activities (AAA) were measured. In leg muscle and liver all measured activities were higher in L as compared to C and control (K) mice. The percent of inhibition of LIA was lower in L then C mice in both examined tissues. In the leg muscles, in L mice protein catabolism was mostly influenced by CatD, but in the liver CatD was mostly active in K mice. CatD, PSCatD, AAA and LIA in leg muscle of L mice as compare to K were higher in female (F) by 68 %, 68.5 %, 91.3 % and 94.5 %, respectively, and in male (M) mice by 43.4 %, 54 %, 47.1 % and 64 %, respectively. The percent of inhibition by leupeptin in AAA was higher in C mice by 61.9 % in F and by 40 % in M mice. In the liver, PIA was higher by about 45 % in L and by 28.5 % in C mice as compare to K ones. There were about 36% of 30.00-39.99 μm muscle fibrils in M mice and in males of L group 40.00-49.99 μm fibrils appeared at 25% (absent in 3 weeks mice). In female, all measured fibril diameters were in higher percent in L than in C group. RNA variables were higher by about 25% (in average) in C as compare to K and L groups. Functional cell size (FCS) was lowered in L and C group as compared to K by about 10 % (in average). These results indicate on faster proteins turnover in L than in C group of mice.

scholarly journals Artificial Intelligence-Based Wearable Robotic Exoskeletons for Upper Limb Rehabilitation: A Review

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2146
Author(s):  
Manuel Andrés Vélez-Guerrero ◽  
Mauro Callejas-Cuervo ◽  
Stefano Mazzoleni
Keyword(s):  
Artificial Intelligence ◽  
Upper Limb ◽  
Main Trend ◽  
Motor Rehabilitation ◽  
Rehabilitation Process ◽  
Upper Limb Rehabilitation ◽  
Multiple Sensors ◽  
Meta Analyses ◽  
Limb Rehabilitation ◽  
And Control

Processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation. This systematic review presents the advances and trends of those technologies. A literature search was performed in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology with three main inclusion criteria: (a) motor or neuromotor rehabilitation for upper limbs, (b) mobile robotic exoskeletons, and (c) AI. The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria. The literature showed the use of artificial neural networks (40%), adaptive algorithms (20%), and other mixed AI techniques (40%). Additionally, it was found that in only 16% of the articles, developments focused on neuromotor rehabilitation. The main trend in the research is the development of wearable robotic exoskeletons (53%) and the fusion of data collected from multiple sensors that enrich the training of intelligent algorithms. There is a latent need to develop more reliable systems through clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.

scholarly journals Similarity Embedding Networks for Robust Human Activity Recognition

2021 ◽  
Vol 15 (6) ◽  
pp. 1-17
Author(s):  
Chenglin Li ◽  
Carrie Lu Tong ◽  
Di Niu ◽  
Bei Jiang ◽  
Xiao Zuo ◽  
...  
Keyword(s):  
Activity Recognition ◽  
Human Activity ◽  
Short Term Memory ◽  
Real Space ◽  
Human Activity Recognition ◽  
Sensor Data ◽  
Activity Data ◽  
Extensive Evaluation ◽  
Sensor Signals ◽  
Public Datasets

Deep learning models for human activity recognition (HAR) based on sensor data have been heavily studied recently. However, the generalization ability of deep models on complex real-world HAR data is limited by the availability of high-quality labeled activity data, which are hard to obtain. In this article, we design a similarity embedding neural network that maps input sensor signals onto real vectors through carefully designed convolutional and Long Short-Term Memory (LSTM) layers. The embedding network is trained with a pairwise similarity loss, encouraging the clustering of samples from the same class in the embedded real space, and can be effectively trained on a small dataset and even on a noisy dataset with mislabeled samples. Based on the learned embeddings, we further propose both nonparametric and parametric approaches for activity recognition. Extensive evaluation based on two public datasets has shown that the proposed similarity embedding network significantly outperforms state-of-the-art deep models on HAR classification tasks, is robust to mislabeled samples in the training set, and can also be used to effectively denoise a noisy dataset.

A Conceptual Design of the Knee Rehabilitation Device

2012 ◽  
Vol 215-216 ◽  
pp. 225-228
Author(s):  
Liang Han ◽  
You Yang Li ◽  
Qian Zhang
Keyword(s):  
Pulse Width Modulation ◽  
Liquid Crystal Display ◽  
Main Body ◽  
Stepping Motor ◽  
Rehabilitation Process ◽  
Knee Rehabilitation ◽  
Body Design ◽  
And Control ◽  
Micro Controller Unit ◽  
The Given

This paper aims to design a knee rehabilitation device which can help the knee patients to perform movement in bending leg manner. And in that way the rehabilitation process will be improved greatly. The design of the device includes the mechanical main body design, driving motor, and control circuit which contains the keyboard setting, display unit and clock unit. Through the pulse width modulation (PWM) technology the stepping motor is driven and the automatic bent in leg is achieved. During the exercise the following information is known: the starting time, the lasting time, the angle of movement and the speed of movement. The micro controller unit (MCU) is responsible for the information processing from both the key and liquid crystal display (LCD). After the key inputs the given parameters the stepping motor can output the desired motions. Meanwhile, the LCD can display the input information. Now the project has accomplished the preliminary design, and the concrete scheme is shown in this paper.

The Achievement of Intelligent Lubrication Adjustment Function of CNC Machine Tools Based on SSAS

2014 ◽  
Vol 556-562 ◽  
pp. 1454-1459
Author(s):  
Dong Sheng You
Keyword(s):  
Machine Tools ◽  
Sensor Data ◽  
Lubricating Oil ◽  
Cnc Machine Tools ◽  
Signal Acquisition ◽  
Cnc Machine ◽  
Lubrication Mode ◽  
Free Function ◽  
And Control ◽  
The Relationship

The use of CNC machine tools signal acquisition, two-way transmission of the temperature sensor data, the ladder design and macro program guide and other methods on the implementation of a temperature sensing system of smart lubrication function. It is not only low-end CNC machine tools can compensate for deficiencies in equipment protection features and maintenance-free function, but also enhance the diversity of processing. Ultimately by analyzing the different lubrication mode, the relationship between the lubricating oil pressure and temperature and other factors, to draw the function in the lubrication in a stabilizing effect on oil pressure and control bearings and nut seat temperature. It is simple and practical, has important theoretical significance and great value.

A Blockchain-Enabled Approach for Online Stream Sensor Data Protection in Cyber-Physical Manufacturing Systems

2021 ◽  
Author(s):  
Zhangyue Shi ◽  
Chenang Liu ◽  
Chen Kan ◽  
Wenmeng Tian ◽  
Yang Chen
Keyword(s):  
Information Technologies ◽  
Manufacturing Systems ◽  
Rapid Development ◽  
Data Access ◽  
Sensor Data ◽  
False Alarms ◽  
Monitoring And Control ◽  
Stream Data ◽  
Physical Security ◽  
And Control

Abstract With the rapid development of the Internet of Things and information technologies, more and more manufacturing systems become cyber-enabled, which significantly improves the flexibility and productivity of manufacturing. Furthermore, a large variety of online sensors are also commonly incorporated in the manufacturing systems for online quality monitoring and control. However, the cyber-enabled environment may pose the collected online stream sensor data under high risks of cyber-physical attacks as well. Specifically, cyber-physical attacks could occur during the manufacturing process to maliciously tamper the sensor data, which could result in false alarms or failures of anomaly detection. In addition, the cyber-physical attacks may also illegally access the collected data without authorization and cause leakage of key information. Therefore, it becomes critical to develop an effective approach to protect online stream data from these attacks so that the cyber-physical security of the manufacturing systems could be assured. To achieve this goal, an integrative blockchain-enabled method, is proposed by leveraging both asymmetry encryption and camouflage techniques. A real-world case study that protects cyber-physical security of collected stream data in additive manufacturing is provided to demonstrate the effectiveness of the proposed method. The results demonstrate that malicious tampering could be detected in a relatively short time and the risk of unauthorized data access is significantly reduced as well.

scholarly journals ADHD and DIRAS Single Nucleotide Polymorphism as an Indicator of Prolonged Concussion Recovery

CommonHealth ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 94-101
Author(s):  
Taziah Kenney ◽  
Jane McDevitt
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Rare Allele ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Adhd Diagnosis ◽  
Hyperactivity Disorder ◽  
Recovery Times ◽  
Prolonged Recovery ◽  
Concussion Recovery ◽  
And Control

The purpose of this study was to determine the association between the presence of a single nucleotide polymorphism (SNP; rs1412005) within DIRAS2 (i.e., a gene associated with attention-deficit/hyperactivity disorder (ADHD) and prolonged recovery following a sport-related concussion. A case-control study design was implemented, where cases and controls were selected from a cohort of 117 deidentified concussed athletes. Eleven samples from this patient cohort self-reported ADHD diagnosis and were age and sex-matched to 22 participants with no self-reported ADHD diagnoses. The average recovery times were 21.50 + 13.96 days and 15.66 + 8.50 days for the case and control groups, respectively. The authors found that only 13.6% of the individuals without an ADHD diagnosis recovered in > 30 days (p = 0.044). Also, the authors found that 72.7% of the carriers of the T allele (i.e., minor allele) recovered in greater than 30 days (p = 0.213).  Researchers concluded that individuals with ADHD had a higher risk of prolonged concussion recovery lasting greater than 30 days. Also, carrying the rare allele was associated with prolonged recovery, which suggests this SNP could be a potential genetic marker for both prolonged concussion recovery and the presence of ADHD.

scholarly journals Effect of Age and Genotype of Native Breed Cockerels on Carcass and Meat Quality

2020 ◽  
Vol 20 (3) ◽  
pp. 1113-1126
Author(s):  
Józefa Krawczyk ◽  
Anna Koseniuk
Keyword(s):  
Meat Quality ◽  
Rhode Island ◽  
Muscle Quality ◽  
Poultry Meat ◽  
Fat Percentage ◽  
Leg Muscles ◽  
Native Breed ◽  
Slaughter Age ◽  
Leg Muscle ◽  
Effect Of Age

AbstractThe aim of the study was to determine meat quality in cockerels of two multipurpose breeds reared to different ages. The study involved 30 cockerels each of two native breeds: Yellowleg Partridge (Ż-33) and Rhode Island Red (R-11). The results showed that cockerels of the native breeds Rhode Island Red (R-11) and Yellowleg Partridge (Ż-33) represent a good starting material for niche production of poultry meat R-11 cockerels exhibited a better rate of weight gain and their carcasses had higher yellowness and redness values compared to Ż-33 birds. The carcasses of both cockerel breeds had lower breast and higher leg muscle percentage, and their meat contained more collagen and protein and less fat. As birds aged, body weight and abdominal fat percentage increased, and giblets percentage decreased in the cockerels of both breeds, whereas in the R-11 breed dressing percentage increased, leg bone percentage decreased, yellowness (a*) increased and redness (b*) decreased. Neither genotype nor slaughter age had a significant effect on chemical composition of the breast and leg muscles. In both breeds, the breast and leg muscle quality traits were more affected by age than genotype.

scholarly journals PENGARUH PELATIHAN 30 SECOND BOX DRILL DAN 60 SECOND BOX DRILL TERHADAP DAYA LEDAK OTOT TUNGKAI

2019 ◽  
Vol 7 (1) ◽  
Author(s):  
Luh Mastia Andriani ◽  
I Gst Lanang Agung Parwata ◽  
Ni Luh Kadek Alit Arsani
Keyword(s):  
Vertical Jump ◽  
Training Group ◽  
T Test ◽  
Control Group ◽  
Control Groups ◽  
Explosive Power ◽  
Jump Test ◽  
Significant Difference ◽  
Leg Muscle ◽  
And Control

Penelitian ini bertujuan untuk mengetahui pengaruh pelatihan 30 second box drill dan 60 second box drill terhadap peningkatan daya ledak otot tungkai. Jenis penelitian ini adalah penelitian eksperimen semu (quasi) dengan rancangan the non-randomized pretest posttest control groups design. Subjek penelitian sebanyak 30 orang. Daya ledak otot tungkai diukur dengan vertical jump test dan data dianalisis dengan uji-t independent, uji anava satu jalur dan uji least significant difference (LSD) pada taraf signifikansi (α) 0,05 dengan bantuan SPSS 16,0. Berdasarkan hasil uji hipotesis antara gaint-score kelompok pelatihan 30 second box drill, 60 second box drill dan kelompok kontrol pada variable daya ledak otot tungkai, hasil analisis data menggunakan uji-t independent menunjukkan bahwa pelatihan 30 second box drill dan 30 second box drill berpengaruh terhadap peningkatan daya ledak otot tungkai dengan nilai signifikansi sebesar 0,000 dan 0,000 (SigKata Kunci : pelatihan 30 second box drill, pelatihan 60 seond box drill, daya ledak otot tungkai This study aimed to know the effect of 30 second box drill training and 60 second box drill training toward the increase of explosive power of leg muscle. This study is quasi experiment research with thenon-randomized pretest posttest control groups design. Subjects of this study were 30 people. The explosive power of leg muscle was measured by vertical jump test and analyzed by independent t-test, one lane anava test and test of least significant difference (LSD) in the significant standard (α) 0,05 by using SPSS 16,0. Based on the result of hypothesis between gaint-score on training group of 30 second box drill, 60 second box drill and control group on the variable of explosive power of leg muscle, result of analysis by using independent t-test showed that 30 second box drill training and 30 second box drill training influenced the explosion power of leg muscle in the significant value of 0,000 and 0,000 (Sigkeyword : 30 second box drill, 60 second box drill,explosive power

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