Force Sensation Induced by Electrical Stimulation of the Tendon of Biceps Muscle

Many wearable interfaces have been proposed to present force to the upper limb and elbow joint. One way to achieve a compact wearable haptic interface is to use electrical stimulation, and we have suggested that transcutaneous electrical stimulation above the wrist tendon can produce force a sensation in the direction of the muscle stretching; however, it has not been investigated in detail whether the force sensation presented by the electrical stimulation of the tendon occurs in the upper limb joints. In this study, to investigate whether the force sensation is generated when applying electrical stimulation of the skin at the tendon or at the muscle belly of the biceps brachii muscle, we quantitatively evaluated the direction and amount of the force sensation under the aforementioned conditions. The results showed that the electrical stimulation of the tendon produced significant force sensation in the direction of elbow extension. On the other hand, in some participants, the electrical stimulation of the muscle belly worked as a supporting force, resulting in the sensation of weakened force perception. In general, we concluded that the sensation produced by muscle stimulation was different from that produced by stimulation of the tendon.

Role of Electromyography(EMG) for (Muscle Conductivity) management of Paralyzed Patients in Dhaka city

The purpose of this study is to assess the electromyography (EMG) signals of biceps muscle of paralyzed patients to know the condition of their affected muscle. For measuring the muscle signal, 5 voltages analog signal is sent to biceps muscle via EMG sensor with Arduino. As higher the voltage is, the condition of the muscle status is better. In this study, we have observed paralyzed patients in Dhaka city having different kinds of paralysis patients like Complete paralysis, Partial or incomplete paralysis and localized paralysis. The study also focused on monitoring different stage of paralysis like Flaccidity, dealing with appearance of spasticity, increased spasticity or decreased spasticity, complex movement combination, spasticity disappear and normal function return. This observational study was carried out in three largest and tertiary care hospitals located in Dhaka metropolitan area with the help of Myoware EMG based muscle sensor. Total 50 paralyzed cases were included in this study. Among the 50 cases of paralyzed patients, majority of the cases (55%) were of 40-55 years aged group where 75% were male and 25% were female. In this study, 85% were Localized paralyzed patients, 10% Partial paralyzed and 5% Complete paralyzed. This study also shows the condition of healthy biceps muscle as compared with paralyzed muscle. The findings of this study could play an important role to observe the condition of paralyzed muscle for better management of paralyzed patients and give a clear idea about which management is needed.

Dynamics of Сhanges in the Power Characteristics of the Biceps Brachii Muscle under the Influence of Different Vibration Effects

Aim. To determine the effects of vibration therapy devices exposure with a constant and aperiodic frequency of vibrations on the tissue of the biceps muscle of the shoulder. Material and methods. The study was conducted on 10 volunteers aged 24-35 years. the program Adobe Audition CC 2020, the device for vibration therapy with a constant vibration frequency “Charm 1-t”, the device for vibration therapy with an aperiodic vibration frequency “Individual massager with a pseudo-boiling layer” (MI EPS), the robotic biomechanical diagnostic and training complex with biological feedback CON-TREX were used. The measurement of the maximum strength of the biceps brachii muscle was carried out once to detect sensitivity to vibration, and then during 7 days for the dynamics of power characteristics. The maximum force was measured before exposure to vibrotherapy devices and immediately after exposure using the isokinetic classical mode of operation of the diagnostic system. Results. In a single measurement of biceps strength on one shoulder in a group of women, the average increase in muscle strength after using the Charm 1-T device was 0.8 N (2.3%), after using MI EPS – 1.9 N (6.4%). In the group of men, the average increase in muscle strength after using the device “Charm 1-T” was 1.9 N (3.2%), after using “MI EPS” – 4.6 N (7.2%). At the seven-day follow-up, the average increase in strength in the group of women on the right hand after using the Charm 1-T device was 21.8% (5.6 N), on the left hand after using MI EPS, the increase was 23.2% (6.1 N). In the group of men, the average increase in strength on the right hand after using “Charm 1-T” was 53% (30.7 N), on the left hand after using “MI EPS” – 15.5% (11.5 N). Conclusion. All participants in the study groups were determined to be sensitive to both types of vibration exposure. The study participants demonstrated an increase in strength indicators when testing the biceps muscle of the shoulder, and there was also an improvement in the tolerability of the procedure itself.

On the Impact of Biceps Muscle Fatigue in Human Activity Recognition

Nowadays, Human Activity Recognition (HAR) systems, which use wearables and smart systems, are a part of our daily life. Despite the abundance of literature in the area, little is known about the impact of muscle fatigue on these systems’ performance. In this work, we use the biceps concentration curls exercise as an example of a HAR activity to observe the impact of fatigue impact on such systems. Our dataset consists of 3000 biceps concentration curls performed and collected from 20 volunteers aged between 20–35. Our findings indicate that fatigue often occurs in later sets of an exercise and extends the completion time of later sets by up to 31% and decreases muscular endurance by 4.1%. Another finding shows that changes in data patterns are often occurring during fatigue presence, causing seven features to become statistically insignificant. Further findings indicate that fatigue can cause a substantial decrease in performance in both subject-specific and cross-subject models. Finally, we observed that a Feedforward Neural Network (FNN) showed the best performance in both cross-subject and subject-specific models in all our evaluations.

Towards Detecting Biceps Muscle Fatigue in Gym Activity Using Wearables

Fatigue is a naturally occurring phenomenon during human activities, but it poses a bigger risk for injuries during physically demanding activities, such as gym activities and athletics. Several studies show that bicep muscle fatigue can lead to various injuries that may require up to 22 weeks of treatment. In this work, we adopt a wearable approach to detect biceps muscle fatigue during a bicep concentration curl exercise as an example of a gym activity. Our dataset consists of 3000 bicep curls from twenty middle-aged volunteers at ages between 27 to 30 and Body Mass Index (BMI) ranging between 18 to 28. All volunteers have been gym-goers for at least 1 year with no records of chronic diseases, muscle, or bone surgeries. We encountered two main challenges while collecting our dataset. The first challenge was the dumbbell’s suitability, where we found that a dumbbell weight (4.5 kg) provides the best tradeoff between longer recording sessions and the occurrence of fatigue on exercises. The second challenge is the subjectivity of RPE, where we average the reported RPE with the measured heart rate converted to RPE. We observed from our data that fatigue reduces the biceps’ angular velocity; therefore, it increases the completion time for later sets. We extracted a total of 33 features from our dataset, which have been reduced to 16 features. These features are the most overall representative and correlated with bicep curl movement, yet they are fatigue-specific features. We utilized these features in five machine learning models, which are Generalized Linear Models (GLM), Logistic Regression (LR), Random Forests (RF), Decision Trees (DT), and Feedforward Neural Networks (FNN). We found that using a two-layer FNN achieves an accuracy of 98% and 88% for subject-specific and cross-subject models, respectively. The results presented in this work are useful and represent a solid start for moving into a real-world application for detecting the fatigue level in bicep muscles using wearable sensors as we advise athletes to take fatigue into consideration to avoid fatigue-induced injuries.

Electromyography Analysis of Muscle Activation During Stand-Up Paddle Boarding: A Comparison of Paddling in Kneeling and Standing Positions

Background: This study aimed to understand individual muscle use in different paddling postures in stand-up paddle boarding (SUP). Methods: Sixteen college students were recruited in this study. Surface electromyography of 16 muscles on the dominant side was recorded. Results: In the time series, the biceps muscle exhibited a continuous activation pattern in the pull phase when kneeling, whereas when standing, the muscle contracted considerably in the exit and recovery phases, implying that it plays different roles in the two postures. The biceps also exhibited significantly higher muscle activation in the kneeling position than it did in the standing position. The maximum muscle activity levels of the external oblique abdominis and triceps were significantly higher when standing than when kneeling. In addition, an unstable SUP board activated the gastrocnemius to help paddlers maintain stability on a swaying surface. Moreover, additional power from the wrist flexor must be used in the recovery and catch phases to stabilize paddle control in the standing position. Conclusion: The knowledge that changes in SUP posture activate different muscle groups can enhance training efficiency and provide a reference for designing individualized training programs.