Real-Time Emg Acquisition and Feature Extraction for Rehabilitation and Prosthesis

Uthvag, S.; Sai, P Vijay; Kumar, Suman; Hariharan, M.; Chanu, Oinam Robita; Raj, V. Karthik

doi:10.4015/s1016237219500376

Cited by 6 publications

(3 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Double threshold (DT): The DT method was applied in the following studies: [ 2 , 10 , 19 – 21 , 24 , 33 , 34 , 42 , 51 , 55 , 65 , 73 , 82 , 83 , 87 , 94 , 95 , 100 , 115 , 119 – 121 , 123 , 127 , 128 , 135 – 151 ].…”

Section: Literature Review Resultsmentioning

confidence: 99%

Review of electromyography onset detection methods for real-time control of robotic exoskeletons

Carvalho,

Fernández,

del-Ama

et al. 2023

J NeuroEngineering Rehabil

View full text Add to dashboard Cite

Background Electromyography (EMG) is a classical technique used to record electrical activity associated with muscle contraction and is widely applied in Biomechanics, Biomedical Engineering, Neuroscience and Rehabilitation Robotics. Determining muscle activation onset timing, which can be used to infer movement intention and trigger prostheses and robotic exoskeletons, is still a big challenge. The main goal of this paper was to perform a review of the state-of-the-art of EMG onset detection methods. Moreover, we compared the performance of the most commonly used methods on experimental EMG data. Methods A total of 156 papers published until March 2022 were included in the review. The papers were analyzed in terms of application domain, pre-processing method and EMG onset detection method. The three most commonly used methods [Single (ST), Double (DT) and Adaptive Threshold (AT)] were applied offline on experimental intramuscular and surface EMG signals obtained during contractions of ankle and knee joint muscles. Results Threshold-based methods are still the most commonly used to detect EMG onset. Compared to ST and AT, DT required more processing time and, therefore, increased onset timing detection, when applied on experimental data. The accuracy of these three methods was high (maximum error detection rate of 7.3%), demonstrating their ability to automatically detect the onset of muscle activity. Recently, other studies have tested different methods (especially Machine Learning based) to determine muscle activation onset offline, reporting promising results. Conclusions This study organized and classified the existing EMG onset detection methods to create consensus towards a possible standardized method for EMG onset detection, which would also allow more reproducibility across studies. The three most commonly used methods (ST, DT and AT) proved to be accurate, while ST and AT were faster in terms of EMG onset detection time, especially when applied on intramuscular EMG data. These are important features towards movement intention identification, especially in real-time applications. Machine Learning methods have received increased attention as an alternative to detect muscle activation onset. However, although several methods have shown their capability offline, more research is required to address their full potential towards real-time applications, namely to infer movement intention.

show abstract

Section: Literature Review Resultsmentioning

confidence: 99%

Review of electromyography onset detection methods for real-time control of robotic exoskeletons

Carvalho,

Fernández,

del-Ama

et al. 2023

J NeuroEngineering Rehabil

View full text Add to dashboard Cite

show abstract

“…Restoring the ability to walk is a main objective in the rehabilitation of a transtibial amputee. Prostheses are used to compensate for the limb's loss and help perform daily activities [1]. The rehabilitation tries to improve the functioning of the remaining limbs to near-normal levels.…”

Section: Introductionmentioning

confidence: 99%

Investigation of EMG Parameters for Transtibial Amputees While Treadmill Walking with Different Speeds: A Preliminary Study

Ghailassi,

Hashim,

Razak

et al. 2024

IEEE Access

View full text Add to dashboard Cite

Electromyography (EMG) is the process of acquiring electrical signals generated through muscle activity (contraction/relaxation). Surface EMG deliberates the amount of electrical activity in the musculoskeletal system in a non-invasive way. Under specific conditions and during certain motor activities, this signal is substantially associated with muscle strength. These Signals are used as Control Inputs by assistive devices. The study aimed to investigate the EMG parameters of lower limb muscles (rectus femoris and biceps femoris) for healthy subjects and transtibial amputees while walking on the treadmill at three different speeds (0.55 m/s, 0.83 m/s, and 1.11 m/s) and to compare the EMG parameters of the rectus and biceps femoris muscles between the healthy subjects and amputees. Ten non-amputee and two transtibial amputee subjects were recruited for this study. The findings indicate substantial reductions in EMG signals at slow speeds, likely to assist with foot stability. The right biceps femoris muscles had the highest signals average for all participants, while the right rectus femoris muscles had the lowest signals average for amputee subject-2 (0.0004 V), throughout the different speeds. The male participants' right biceps femoris muscle showed the greatest signals of average treadmill walking activity at 0,55 m/s (0.0014 V) compared to the amputee individuals' (0.001 V). At (0,83 m/s), male participants (0.0015 V) outperformed amputee subjects (0.0004 V). At (1,11 m/s), male participants (0.0024 V) outperformed amputee subjects (0.001 V). The assessment of the influence of this study can be used to assist in the rehabilitation treatment of a transtibial amputee, taking into account distance and maximum speed while using the prosthesis.INDEX TERMS Treadmill walking, transtibial amputee, electromyography, slow speed.

show abstract

“…Electromyography (EMG) is one of the manners used in gait analysis, many different activities and an assortment of implementations, including EMG for upper and lower limb prostheses. 5–12 According to lower-limb amputees, prosthetics, including EMG within the socket, can provide a method to predict the user’s movement. Based on this level of continuous sensing, it gives us a continuous signal, which is sent to the controller to give the necessary command for the required movement.…”

Section: Introductionmentioning

confidence: 99%

Investigation of EMG parameter for transtibial prosthetic user with flexion and extension of the knee and normal walking gait: A preliminary study

Sobh

Razak

Osman

2021

Proc Inst Mech Eng H

View full text Add to dashboard Cite

Electromyography signal has been used widely as input for prosthetic’s leg movements. C-Leg, for example, is among the prosthetics devices that use electromyography as the main input. The main challenge facing the industrial party is the position of the electromyography sensor as it is fixed inside the socket. The study aims to investigate the best positional parameter of electromyography for transtibial prosthetic users for the device to be effective in multiple movement activities and compare with normal human muscle’s activities. DELSYS Trigno wireless electromyography instrument was used in this study to achieve this aim. Ten non-amputee subjects and two transtibial amputees were involved in this study. The surface electromyography signals were recorded from two anterior and posterior below the knee muscles and above the knee muscles, respectively: tibial anterior and gastrocnemius lateral head as well as rectus femoris and biceps femoris during two activities (flexion and extension of knee joint and gait cycle for normal walking). The result during flexion and extension activities for gastrocnemius lateral head and biceps femoris muscles was found to be more useful for the control subjects, while the tibial anterior and also gastrocnemius lateral head are more active for amputee subjects. Also, during normal walking activity for biceps femoris and gastrocnemius lateral head, it was more useful for the control subjects, while for transtibial amputee subject-1, the rectus femoris was the highest signal of the average normal walking activity (0.0001 V) compared to biceps femoris (0.00007 V), as for transtibial amputee subject-2, the biceps femoris was the highest signals of the average normal walking activity (0.0001 V) compared to rectus femoris (0.00004 V). So, it is difficult to rely entirely on the static positioning of the electromyography sensor within the socket as there is a possibility of the sensor to contact with inactive muscle, which will be a gap in the control, leading to a decrease in the functional efficiency of the powered prostheses.

show abstract

Real-Time Emg Acquisition and Feature Extraction for Rehabilitation and Prosthesis

Cited by 6 publications

References 26 publications

Review of electromyography onset detection methods for real-time control of robotic exoskeletons

Review of electromyography onset detection methods for real-time control of robotic exoskeletons

Investigation of EMG Parameters for Transtibial Amputees While Treadmill Walking with Different Speeds: A Preliminary Study

Investigation of EMG parameter for transtibial prosthetic user with flexion and extension of the knee and normal walking gait: A preliminary study

Contact Info

Product

Resources

About