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Статті в журналах з теми "Force myography"

Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 травня 2022

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1

Curcio, Brittney C., Nicholas V. Cirillo, and Michael Wininger. "Force Myography across Socket Material." Journal of Prosthetics and Orthotics 32, no. 1 (January 2020): 52–58. http://dx.doi.org/10.1097/jpo.0000000000000295.

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2

Jiang, Xianta, Lukas-Karim Merhi, and Carlo Menon. "Force Exertion Affects Grasp Classification Using Force Myography." IEEE Transactions on Human-Machine Systems 48, no. 2 (April 2018): 219–26. http://dx.doi.org/10.1109/thms.2017.2693245.

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3

Godiyal, Anoop Kant, Upinderpal Singh, Sneh Anand, and Deepak Joshi. "Analysis of force myography based locomotion patterns." Measurement 140 (July 2019): 497–503. http://dx.doi.org/10.1016/j.measurement.2019.04.009.

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4

Stokes, M. J., and P. A. Dalton. "Acoustic myography for investigating human skeletal muscle fatigue." Journal of Applied Physiology 71, no. 4 (October 1, 1991): 1422–26. http://dx.doi.org/10.1152/jappl.1991.71.4.1422.

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Sounds produced during voluntary isometric contractions of the quadriceps muscle were studied by acoustic myography (AMG) in five healthy adults. With the subject seated, isometric force, surface electromyography (EMG), and AMG were recorded over rectus femoris, and the EMG and AMG signals were integrated (IEMG and IAMG). Contractions lasting 5 s each were performed at 10, 25, 50, 60, 75, and 100% of maximum voluntary contraction (MVC) force. Fatigue was then induced by repeated voluntary contractions (10 s on, 10 s off) at 75% MVC until only 40% MVC could be sustained. After 15 min of rest, the different force levels were again tested in relation to the fresh MVC. Both before and after fatiguing activity the relationships between force and IEMG [r = 0.99 +/- 0.01 (SD), n = 10] and force and IAMG (r = 0.98 +/- 0.02) were linear. After activity, however, the slopes of the regression lines for force and IEMG increased (P less than 0.01) but those for force and IAMG remained the same (P greater than 0.05). The present results clarify the relationship between AMG and isometric force in fatigued muscle without the problem of fatigue-induced tremor, which hampered previous studies of prolonged activity. This study contributes to the validation of AMG and shows that it is a potentially useful method for noninvasive assessment of force production and fatigue. Further studies to establish the origin of AMG activity are required before AMG can be accepted for use in neuromuscular physiology or rehabilitation.

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5

Xiao, Zhen Gang, and Carlo Menon. "A Review of Force Myography Research and Development." Sensors 19, no. 20 (October 20, 2019): 4557. http://dx.doi.org/10.3390/s19204557.

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Information about limb movements can be used for monitoring physical activities or for human-machine-interface applications. In recent years, a technique called Force Myography (FMG) has gained ever-increasing traction among researchers to extract such information. FMG uses force sensors to register the variation of muscle stiffness patterns around a limb during different movements. Using machine learning algorithms, researchers are able to predict many different limb activities. This review paper presents state-of-art research and development on FMG technology in the past 20 years. It summarizes the research progress in both the hardware design and the signal processing techniques. It also discusses the challenges that need to be solved before FMG can be used in an everyday scenario. This paper aims to provide new insight into FMG technology and contribute to its advancement.

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6

Godiyal, Anoop Kant, Milton Mondal, Shiv Dutt Joshi, and Deepak Joshi. "Force Myography Based Novel Strategy for Locomotion Classification." IEEE Transactions on Human-Machine Systems 48, no. 6 (December 2018): 648–57. http://dx.doi.org/10.1109/thms.2018.2860598.

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7

Kadkhodayan, Anita, Xianta Jiang, and Carlo Menon. "Continuous Prediction of Finger Movements Using Force Myography." Journal of Medical and Biological Engineering 36, no. 4 (July 29, 2016): 594–604. http://dx.doi.org/10.1007/s40846-016-0151-y.

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8

Chu, Kelvin HT, Xianta Jiang, and Carlo Menon. "Wearable step counting using a force myography-based ankle strap." Journal of Rehabilitation and Assistive Technologies Engineering 4 (January 2017): 205566831774630. http://dx.doi.org/10.1177/2055668317746307.

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Introduction Step counting can be used to estimate the activity level of people in daily life; however, commercially available accelerometer-based step counters have shown inaccuracies in detection of low-speed walking steps (<2.2 km/h), and thus are not suitable for older adults who usually walk at low speeds. This proof-of-concept study explores the feasibility of using force myography recorded at the ankle to detect low-speed steps. Methods Eight young healthy participants walked on a treadmill at three speeds (1, 1.5, and 2.0 km/h) while their force myography signals were recorded at the ankle using a customized strap embedded with an array of eight force-sensing resistors. A K-nearest neighbour model was trained and tested with the recorded data. Additional three mainstream machine learning algorithms were also employed to evaluate the performance of force myography band as a pedometer. Results Results showed a low error rate of the step detection (<1.5%) at all three walking speeds. Conclusions This study demonstrates not only the feasibility of the proposed approach but also the potential of the investigated technology to reliably monitor low-speed step counting.

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9

Belyea, Alexander T., Kevin B. Englehart, and Erik J. Scheme. "A proportional control scheme for high density force myography." Journal of Neural Engineering 15, no. 4 (June 19, 2018): 046029. http://dx.doi.org/10.1088/1741-2552/aac89b.

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10

Prakash, Alok, Neeraj Sharma, and Shiru Sharma. "An affordable transradial prosthesis based on force myography sensor." Sensors and Actuators A: Physical 325 (July 2021): 112699. http://dx.doi.org/10.1016/j.sna.2021.112699.

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11

Sanford, Joe, Rita Patterson, and Dan O. Popa. "Concurrent surface electromyography and force myography classification during times of prosthetic socket shift and user fatigue." Journal of Rehabilitation and Assistive Technologies Engineering 4 (January 2017): 205566831770873. http://dx.doi.org/10.1177/2055668317708731.

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Objective Surface electromyography has been a long-standing source of signals for control of powered prosthetic devices. By contrast, force myography is a more recent alternative to surface electromyography that has the potential to enhance reliability and avoid operational challenges of surface electromyography during use. In this paper, we report on experiments conducted to assess improvements in classification of surface electromyography signals through the addition of collocated force myography consisting of piezo-resistive sensors. Methods Force sensors detect intrasocket pressure changes upon muscle activation due to changes in muscle volume during activities of daily living. A heterogeneous sensor configuration with four surface electromyography–force myography pairs was investigated as a control input for a powered upper limb prosthetic. Training of two different multilevel neural perceptron networks was employed during classification and trained on data gathered during experiments simulating socket shift and muscle fatigue. Results Results indicate that intrasocket pressure data used in conjunction with surface EMG data can improve classification of human intent and control of a powered prosthetic device compared to traditional, surface electromyography only systems. Significance Additional sensors lead to significantly better signal classification during times of user fatigue, poor socket fit, as well as radial and ulnar wrist deviation. Results from experimentally obtained training data sets are presented.

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12

Bellemare, François, Jacques Couture, François Donati, and Benoît Plaud. "Temporal Relation between Acoustic and Force Responses at the Adductor Pollicis during Nondepolarizing Neuromuscular Block." Anesthesiology 93, no. 3 (September 1, 2000): 646–52. http://dx.doi.org/10.1097/00000542-200009000-00012.

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Background Contracting muscle emits sounds. The purpose of this study was to compare the time course of muscular paralysis at the adductor pollicis muscle (AP) with use of acoustic myography and mechanomyography. Methods Thirteen elective surgery patients, American Society of Anesthesiologists physical status I, received rocuronium (0.6 mg/kg intravenously) as a bolus dose during general anesthesia. Force of AP was measured with use of a strain gauge, and sounds were recorded simultaneously with use of a small condenser microphone fixed on the palmar surface of the hand over the AP. Supramaximal stimulation was applied to the ulnar nerve at 0.1 Hz for 45-60 min. In seven patients, the response to train-of-four stimulation was also recorded during recovery. Results Force and sounds both were equally sensitive in measuring maximum block. The relation between sound and force was curvilinear, with good agreement near 0 and 100% and acoustic response exceeding mechanical response at intermediate levels of block. The acoustic signal had a slower onset and a faster recovery than the force response. The fade response of sound to train-of-four stimulation also recovered faster than that of force. Conclusion Acoustic myography is an alternative method to monitor muscular paralysis that is easy to set up and applicable to most superficial muscles. However, the time course of relaxation at AP using acoustic myography differs from the time course of force relaxation. Therefore, these two methods are not equivalent when applied to AP.

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13

Zakia, Umme, and Carlo Menon. "Force Myography-Based Human Robot Interactions via Deep Domain Adaptation and Generalization." Sensors 22, no. 1 (December 29, 2021): 211. http://dx.doi.org/10.3390/s22010211.

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Estimating applied force using force myography (FMG) technique can be effective in human-robot interactions (HRI) using data-driven models. A model predicts well when adequate training and evaluation are observed in same session, which is sometimes time consuming and impractical. In real scenarios, a pretrained transfer learning model predicting forces quickly once fine-tuned to target distribution would be a favorable choice and hence needs to be examined. Therefore, in this study a unified supervised FMG-based deep transfer learner (SFMG-DTL) model using CNN architecture was pretrained with multiple sessions FMG source data (Ds, Ts) and evaluated in estimating forces in separate target domains (Dt, Tt) via supervised domain adaptation (SDA) and supervised domain generalization (SDG). For SDA, case (i) intra-subject evaluation (Ds ≠ Dt-SDA, Ts ≈ Tt-SDA) was examined, while for SDG, case (ii) cross-subject evaluation (Ds ≠ Dt-SDG, Ts ≠ Tt-SDG) was examined. Fine tuning with few “target training data” calibrated the model effectively towards target adaptation. The proposed SFMG-DTL model performed better with higher estimation accuracies and lower errors (R2 ≥ 88%, NRMSE ≤ 0.6) in both cases. These results reveal that interactive force estimations via transfer learning will improve daily HRI experiences where “target training data” is limited, or faster adaptation is required.

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14

IGARASHI, Tatsuya, Kazuhiro FUJISAKI, Kazuhiko SASAGAWA, and Takeshi MORIWAKI. "Force Myography analysis of muscle fatigue characteristics during hand motion." Proceedings of the JSME Conference on Frontiers in Bioengineering 2018.29 (2018): 1B25. http://dx.doi.org/10.1299/jsmebiofro.2018.29.1b25.

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15

Tortopidis, D., M. F. Lyons, and R. H. Baxendale. "Acoustic myography, electromyography and bite force in the masseter muscle." Journal of Oral Rehabilitation 25, no. 12 (December 1998): 940–45. http://dx.doi.org/10.1046/j.1365-2842.1998.00338.x.

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16

Fujiwara, Eric, Yu Tzu Wu, Murilo F. M. Santos, Egont A. Schenkel, and Carlos K. Suzuki. "Optical Fiber Specklegram Sensor for Measurement of Force Myography Signals." IEEE Sensors Journal 17, no. 4 (February 15, 2017): 951–58. http://dx.doi.org/10.1109/jsen.2016.2638831.

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17

Fujiwara, Eric, and Carlos Kenichi Suzuki. "Optical Fiber Force Myography Sensor for Identification of Hand Postures." Journal of Sensors 2018 (2018): 1–10. http://dx.doi.org/10.1155/2018/8940373.

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A low-cost optical fiber force myography sensor for noninvasive hand posture identification is proposed. The transducers are comprised of 10 mm periodicity silica multimode fiber microbending devices mounted in PVC plates, providing 0.05 N−1 sensitivity over ~20 N range. Next, the transducers were attached to the user forearm by means of straps in order to monitor the posterior proximal radial, the anterior medial ulnar, and the posterior distal radial muscles, and the acquired FMG optical signals were correlated to the performed gestures using a 5 hidden layers, 20-neuron artificial neural network classifier with backpropagation architecture, followed by a competitive layer. The overall results for 9 postures and 6 subjects indicated a 98.4% sensitivity and 99.7% average accuracy, being comparable to the electromyographic approaches. Moreover, in contrast to the current setups, the proposed methodology allows the identification of poses characterized by different configurations of fingers and wrist joint displacements with the utilization of only 3 transducers and a simple interrogation scheme, being suitable to further applications in human-computer interfaces.

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18

Prakash, Alok, Ajay Kumar Sahi, Neeraj Sharma, and Shiru Sharma. "Force myography controlled multifunctional hand prosthesis for upper-limb amputees." Biomedical Signal Processing and Control 62 (September 2020): 102122. http://dx.doi.org/10.1016/j.bspc.2020.102122.

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19

Ribas Neto, Antonio, Julio Fajardo, Willian Hideak Arita da Silva, Matheus Kaue Gomes, Maria Claudia Ferrari de Castro, Eric Fujiwara, and Eric Rohmer. "Design of Tendon-Actuated Robotic Glove Integrated with Optical Fiber Force Myography Sensor." Automation 2, no. 3 (September 3, 2021): 187–201. http://dx.doi.org/10.3390/automation2030012.

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People taken by upper limb disorders caused by neurological diseases suffer from grip weakening, which affects their quality of life. Researches on soft wearable robotics and advances in sensor technology emerge as promising alternatives to develop assistive and rehabilitative technologies. However, current systems rely on surface electromyography and complex machine learning classifiers to retrieve the user intentions. In addition, the grasp assistance through electromechanical or fluidic actuators is passive and does not contribute to the rehabilitation of upper-limb muscles. Therefore, this paper presents a robotic glove integrated with a force myography sensor. The glove-like orthosis features tendon-driven actuation through servo motors, working as an assistive device for people with hand disabilities. The detection of user intentions employs an optical fiber force myography sensor, simplifying the operation beyond the usual electromyography approach. Moreover, the proposed system applies functional electrical stimulation to activate the grasp collaboratively with the tendon mechanism, providing motion support and assisting rehabilitation.

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20

Jiang, Xianta, Kelvin Chu, Mahta Khoshnam, and Carlo Menon. "A Wearable Gait Phase Detection System Based on Force Myography Techniques." Sensors 18, no. 4 (April 21, 2018): 1279. http://dx.doi.org/10.3390/s18041279.

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21

Jiang, Xianta, Lukas-Karim Merhi, Zhen Gang Xiao, and Carlo Menon. "Exploration of Force Myography and surface Electromyography in hand gesture classification." Medical Engineering & Physics 41 (March 2017): 63–73. http://dx.doi.org/10.1016/j.medengphy.2017.01.015.

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22

Jiang, Xianta, Zhen Gang Xiao, and Carlo Menon. "Virtual grasps recognition using fusion of Leap Motion and force myography." Virtual Reality 22, no. 4 (March 1, 2018): 297–308. http://dx.doi.org/10.1007/s10055-018-0339-2.

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23

Zakia, Umme, and Carlo Menon. "Human–Robot Collaboration in 3D via Force Myography Based Interactive Force Estimations Using Cross-Domain Generalization." IEEE Access 10 (2022): 35835–45. http://dx.doi.org/10.1109/access.2022.3164103.

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24

Xiao, Zhen Gang, and Carlo Menon. "Counting Grasping Action Using Force Myography: An Exploratory Study With Healthy Individuals." JMIR Rehabilitation and Assistive Technologies 4, no. 1 (May 16, 2017): e5. http://dx.doi.org/10.2196/rehab.6901.

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25

Radmand, Ashkan, Erik Scheme, and Kevin Englehart. "High-density force myography: A possible alternative for upper-limb prosthetic control." Journal of Rehabilitation Research and Development 53, no. 4 (2016): 443–56. http://dx.doi.org/10.1682/jrrd.2015.03.0041.

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26

Wu, Yu Tzu, Matheus K. Gomes, Willian HA da Silva, Pedro M. Lazari, and Eric Fujiwara. "Integrated Optical Fiber Force Myography Sensor as Pervasive Predictor of Hand Postures." Biomedical Engineering and Computational Biology 11 (January 2020): 117959722091282. http://dx.doi.org/10.1177/1179597220912825.

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Force myography (FMG) is an appealing alternative to traditional electromyography in biomedical applications, mainly due to its simpler signal pattern and immunity to electrical interference. Most FMG sensors, however, send data to a computer for further processing, which reduces the user mobility and, thus, the chances for practical application. In this sense, this work proposes to remodel a typical optical fiber FMG sensor with smaller portable components. Moreover, all data acquisition and processing routines were migrated to a Raspberry Pi 3 Model B microprocessor, ensuring the comfort of use and portability. The sensor was successfully demonstrated for 2 input channels and 9 postures classification with an average precision and accuracy of ~99.5% and ~99.8%, respectively, using a feedforward artificial neural network of 2 hidden layers and a competitive output layer.

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27

Prakash, Alok, Neeraj Sharma, and Shiru Sharma. "Novel force myography sensor to measure muscle contractions for controlling hand prostheses." Instrumentation Science & Technology 48, no. 1 (August 21, 2019): 43–62. http://dx.doi.org/10.1080/10739149.2019.1655441.

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28

FUJISAKI, Kazuhiro, Ayane KONDO, Kazuhiko SASAGAWA, and Takeshi MORIWAKI. "Development of compact pressing system for muscle activity evaluation in force myography." Mechanical Engineering Letters 7 (2021): 21–00283. http://dx.doi.org/10.1299/mel.21-00283.

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29

Rodrigues, Matheus S., Pedro M. Lazari, Marco C. P. Soares, and Eric Fujiwara. "Characterization of Hand Gestures by a Smartphone-Based Optical Fiber Force Myography Sensor." Engineering Proceedings 2, no. 1 (November 14, 2020): 46. http://dx.doi.org/10.3390/ecsa-7-08178.

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In this paper, a smartphone-integrated, optical fiber sensor based on the force myography technique (FMG), which characterizes the stimuli of the forearm muscles in terms of mechanical pressures, was proposed for the identification of hand gestures. The device’s flashlight excites a pair of polymer optical fibers and the output signals are detected by the camera. The light intensity is modulated through wearable, force-driven microbending transducers placed in the forearm and the acquired optical signals are processed by an algorithm based on decision trees and residual error. The sensor provided a hit rate of 87% regarding four postures, yielding reliable performance with a simple, portable, and low-cost setup embedded on a smartphone.

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30

Lei, Guangtai, Shenyilang Zhang, Yinfeng Fang, Yuxi Wang, and Xuguang Zhang. "Investigation on the Sampling Frequency and Channel Number for Force Myography Based Hand Gesture Recognition." Sensors 21, no. 11 (June 3, 2021): 3872. http://dx.doi.org/10.3390/s21113872.

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Force myography (FMG) is a method that uses pressure sensors to measure muscle contraction indirectly. Compared with the conventional approach utilizing myoelectric signals in hand gesture recognition, it is a valuable substitute. To achieve the aim of gesture recognition at minimum cost, it is necessary to study the minimum sampling frequency and the minimal number of channels. For purpose of investigating the effect of sampling frequency and the number of channels on the accuracy of gesture recognition, a hardware system that has 16 channels has been designed for capturing forearm FMG signals with a maximum sampling frequency of 1 kHz. Using this acquisition equipment, a force myography database containing 10 subjects’ data has been created. In this paper, gesture accuracies under different sampling frequencies and channel’s number are obtained. Under 1 kHz sampling rate and 16 channels, four of five tested classifiers reach an accuracy up to about 99%. Other experimental results indicate that: (1) the sampling frequency of the FMG signal can be as low as 5 Hz for the recognition of static movements; (2) the reduction of channel number has a large impact on the accuracy, and the suggested channel number for gesture recognition is eight; and (3) the distribution of the sensors on the forearm would affect the recognition accuracy, and it is possible to improve the accuracy via optimizing the sensor position.

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31

Grushko, Stefan, Tomáš Spurný, and Martin Černý. "Control Methods for Transradial Prostheses Based on Remnant Muscle Activity and Its Relationship with Proprioceptive Feedback." Sensors 20, no. 17 (August 28, 2020): 4883. http://dx.doi.org/10.3390/s20174883.

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The loss of a hand can significantly affect one’s work and social life. For many patients, an artificial limb can improve their mobility and ability to manage everyday activities, as well as provide the means to remain independent. This paper provides an extensive review of available biosensing methods to implement the control system for transradial prostheses based on the measured activity in remnant muscles. Covered techniques include electromyography, magnetomyography, electrical impedance tomography, capacitance sensing, near-infrared spectroscopy, sonomyography, optical myography, force myography, phonomyography, myokinetic control, and modern approaches to cineplasty. The paper also covers combinations of these approaches, which, in many cases, achieve better accuracy while mitigating the weaknesses of individual methods. The work is focused on the practical applicability of the approaches, and analyses present challenges associated with each technique along with their relationship with proprioceptive feedback, which is an important factor for intuitive control over the prosthetic device, especially for high dexterity prosthetic hands.

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32

Ferigo, Diego, Lukas-Karim Merhi, Brittany Pousett, Zhen Gang Xiao, and Carlo Menon. "A Case Study of a Force-myography Controlled Bionic Hand Mitigating Limb Position Effect." Journal of Bionic Engineering 14, no. 4 (December 2017): 692–705. http://dx.doi.org/10.1016/s1672-6529(16)60435-3.

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33

Godiyal, Anoop Kant, Hemant Kumar Verma, Nitin Khanna, and Deepak Joshi. "A Force Myography-Based System for Gait Event Detection in Overground and Ramp Walking." IEEE Transactions on Instrumentation and Measurement 67, no. 10 (October 2018): 2314–23. http://dx.doi.org/10.1109/tim.2018.2816799.

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34

Goldenberg, M. S., H. J. Yack, F. J. Cerny, and H. W. Burton. "Acoustic myography as an indicator of force during sustained contractions of a small hand muscle." Journal of Applied Physiology 70, no. 1 (January 1, 1991): 87–91. http://dx.doi.org/10.1152/jappl.1991.70.1.87.

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To test the hypothesis that muscle sound amplitudes would remain constant during sustained submaximal isometric contractions, we recorded acoustic myograms from the abductor digiti minimi muscle in 12 subjects at 15, 25, 50, and 75% of a maximum voluntary contraction (MVC). Muscle sounds were detected with an omni-directional electret microphone encased in closed-cell foam and attached to the skin over the muscle. Acoustic amplitudes from the middle and end of the sustained contractions were compared with the amplitudes from the beginning of contractions to determine whether acoustic amplitudes varied in magnitude as force remained constant. Physiological tremor was eliminated from the acoustic signal by use of a Fourier truncation at 14 Hz. The amplitudes of the acoustic signal at a contraction intensity of 75% MVC remained constant, reflecting force production over time. At 50% MVC, the root-mean-square amplitude decreased from the beginning to the end of the contraction (P less than 0.05). Acoustic amplitudes increased over time at 15 and 25% MVC and were significantly higher at the end of the contractions than at the beginning (P less than 0.05). Alterations in the acoustic amplitude, which reflect changes in the lateral vibrations of the muscle, may be indicative of the different recruitment strategies used to maintain force during sustained isometric contractions.

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35

Zakia, Umme, and Carlo Menon. "Estimating Exerted Hand Force via Force Myography to Interact with a Biaxial Stage in Real-Time by Learning Human Intentions: A Preliminary Investigation." Sensors 20, no. 7 (April 8, 2020): 2104. http://dx.doi.org/10.3390/s20072104.

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Force myography (FMG) signals can read volumetric changes of muscle movements, while a human participant interacts with the environment. For collaborative activities, FMG signals could potentially provide a viable solution to controlling manipulators. In this paper, a novel method to interact with a two-degree-of-freedom (DoF) system consisting of two perpendicular linear stages using FMG is investigated. The method consists in estimating exerted hand forces in dynamic arm motions of a participant using FMG signals to provide velocity commands to the biaxial stage during interactions. Five different arm motion patterns with increasing complexities, i.e., “x-direction”, “y-direction”, “diagonal”, “square”, and “diamond”, were considered as human intentions to manipulate the stage within its planar workspace. FMG-based force estimation was implemented and evaluated with a support vector regressor (SVR) and a kernel ridge regressor (KRR). Real-time assessments, where 10 healthy participants were asked to interact with the biaxial stage by exerted hand forces in the five intended arm motions mentioned above, were conducted. Both the SVR and the KRR obtained higher estimation accuracies of 90–94% during interactions with simple arm motions (x-direction and y-direction), while for complex arm motions (diagonal, square, and diamond) the notable accuracies of 82–89% supported the viability of the FMG-based interactive control.

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Xiao, Zhen Gang, and Carlo Menon. "Does force myography recorded at the wrist correlate to resistance load levels during bicep curls?" Journal of Biomechanics 83 (January 2019): 310–14. http://dx.doi.org/10.1016/j.jbiomech.2018.11.035.

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37

Azeez, T. A., M. R. Andrade, and J. D. La Favor. "Optimal Wire Myography Normalization for the Rat Dorsal Penile, Internal Pudendal and Internal Iliac Arteries." Physiological Research, no. 6 (December 21, 2021): 931–37. http://dx.doi.org/10.33549//physiolres.934714.

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In functional arterial studies using wire myography, the determination of a vessel’s standardized normalization factor (factor k) is an essential step to ensure optimal contraction and relaxation by the arteries when stimulated with their respective vasoactive agents and to obtain reproducible results. The optimal factor k for several arteries have been determined; however, the optimal initial tension and factor k for the arteries involved in erection remains unknown. Hence, in the present study we set out to determine the optimal factor k for the internal iliac artery, proximal and distal internal pudendal artery (IPA), and dorsal penile artery. After isolating, harvesting, and mounting the arteries from male Sprague-Dawley rats on a multi wire myograph, we tested arterial responsivity to high K+-stimulation when the factor k was set at 0.7, 0.8, 0.85, 0.9, 0.95, 1.0, 1.1, and 1.2 to determine the factor k setting that results in the greatest K+-induced active force production for each vessel type. The data showed the optimal factor k is 0.90-0.95 for the dorsal penile, distal internal pudendal and internal iliac arteries while it is 0.85-0.90 for proximal internal pudendal artery. These optimal values corresponded to initial passive tension settings of 1.10±0.16 - 1.46±0.23, 1.28±0.20 - 1.69±0.34, 1.03±0.27 - 1.33±0.31, and 1.33±0.31 - 1.77±0.43 mN/mm for the dorsal penile, distal IP, proximal IP, and internal iliac arteries, respectively.

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38

Ngo, Chuong, Carlos Munoz, Markus Lueken, Alfred Hülkenberg, Cornelius Bollheimer, Andrey Briko, Alexander Kobelev, Sergey Shchukin, and Steffen Leonhardt. "A Wearable, Multi-Frequency Device to Measure Muscle Activity Combining Simultaneous Electromyography and Electrical Impedance Myography." Sensors 22, no. 5 (March 2, 2022): 1941. http://dx.doi.org/10.3390/s22051941.

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The detection of muscle contraction and the estimation of muscle force are essential tasks in robot-assisted rehabilitation systems. The most commonly used method to investigate muscle contraction is surface electromyography (EMG), which, however, shows considerable disadvantages in predicting the muscle force, since unpredictable factors may influence the detected force but not necessarily the EMG data. Electrical impedance myography (EIM) investigates the change in electrical impedance during muscle activities and is another promising technique to investigate muscle functions. This paper introduces the design, development, and evaluation of a device that performs EMG and EIM simultaneously for more robust measurement of muscle conditions subject to artifacts. The device is light, wearable, and wireless and has a modular design, in which the EMG, EIM, micro-controller, and communication modules are stacked and interconnected through connectors. As a result, the EIM module measures the bioimpedance between 20 and 200 Ω with an error of less than 5% at 140 SPS. The settling time during the calibration phase of this module is less than 1000 ms. The EMG module captures the spectrum of the EMG signal between 20–150 Hz at 1 kSPS with an SNR of 67 dB. The micro-controller and communication module builds an ARM-Cortex M3 micro-controller which reads and transfers the captured data every 1 ms over RF (868 Mhz) with a baud rate of 500 kbps to a receptor connected to a PC. Preliminary measurements on a volunteer during leg extension, walking, and sit-to-stand showed the potential of the system to investigate muscle function by combining simultaneous EMG and EIM.

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Smith, T. G., and M. J. Stokes. "Technical aspects of acoustic myography (AMG) of human skeletal muscle: contact pressure and force/AMG relationships." Journal of Neuroscience Methods 47, no. 1-2 (April 1993): 85–92. http://dx.doi.org/10.1016/0165-0270(93)90024-l.

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40

Esposito, Daniele, Jessica Centracchio, Emilio Andreozzi, Sergio Savino, Gaetano D. Gargiulo, Ganesh R. Naik, and Paolo Bifulco. "Design of a 3D-Printed Hand Exoskeleton Based on Force-Myography Control for Assistance and Rehabilitation." Machines 10, no. 1 (January 13, 2022): 57. http://dx.doi.org/10.3390/machines10010057.

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Voluntary hand movements are usually impaired after a cerebral stroke, affecting millions of people per year worldwide. Recently, the use of hand exoskeletons for assistance and motor rehabilitation has become increasingly widespread. This study presents a novel hand exoskeleton, designed to be low cost, wearable, easily adaptable and suitable for home use. Most of the components of the exoskeleton are 3D printed, allowing for easy replication, customization and maintenance at a low cost. A strongly underactuated mechanical system allows one to synergically move the four fingers by means of a single actuator through a rigid transmission, while the thumb is kept in an adduction or abduction position. The exoskeleton’s ability to extend a typical hypertonic paretic hand of stroke patients was firstly tested using the SimScape Multibody simulation environment; this helped in the choice of a proper electric actuator. Force-myography was used instead of the standard electromyography to voluntarily control the exoskeleton with more simplicity. The user can activate the flexion/extension of the exoskeleton by a weak contraction of two antagonist muscles. A symmetrical master–slave motion strategy (i.e., the paretic hand motion is activated by the healthy hand) is also available for patients with severe muscle atrophy. An inexpensive microcontroller board was used to implement the electronic control of the exoskeleton and provide feedback to the user. The entire exoskeleton including batteries can be worn on the patient’s arm. The ability to provide a fluid and safe grip, like that of a healthy hand, was verified through kinematic analyses obtained by processing high-framerate videos. The trajectories described by the phalanges of the natural and the exoskeleton finger were compared by means of cross-correlation coefficients; a similarity of about 80% was found. The time required for both closing and opening of the hand exoskeleton was about 0.9 s. A rigid cylindric handlebar containing a load cell measured an average power grasp force of 94.61 N, enough to assist the user in performing most of the activities of daily living. The exoskeleton can be used as an aid and to promote motor function recovery during patient’s neurorehabilitation therapy.

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Ogawa, Haruo, Junya Kusumoto, Tadashi Nomura, Kazunobu Hashikawa, Hiroto Terashi, and Shunsuke Sakakibara. "Wire Myography for Continuous Estimation of the Optimal Concentration of Topical Lidocaine as a Vasodilator in Microsurgery." Journal of Reconstructive Microsurgery 37, no. 06 (January 31, 2021): 541–50. http://dx.doi.org/10.1055/s-0040-1722759.

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Abstract Background Intraoperative vasospasm during reconstructive microvascular surgery is often unpredictable and may lead to devastating flap loss. Therefore, various vasodilators are used in reconstructive microsurgery to prevent and relieve vasospasm. Lidocaine is a vasodilator commonly used in microvascular surgery. Although many reports have described its in vitro and in vivo concentration-dependent vasodilatory effects, limited studies have examined the pharmacological effects of lidocaine on blood vessels in terms of persistence and titer. Methods In this study, the vasodilatory effect of lidocaine was examined by using the wire myograph system. Abdominal aortas were harvested from female rats, sliced into rings of 1-mm thickness, and mounted in the wire myograph system. Next, 10, 5, 2, and 1% lidocaine solutions were applied to the artery, and the change in vasodilation force, persistence of the force, and time required to reach equilibrium were measured. Results The vasodilatory effect was confirmed in all groups following lidocaine treatment. Although strong vasodilation was observed in the 10% lidocaine group, it was accompanied by irreversible degeneration of the artery. Vasodilation in the 1% lidocaine group was weaker than that in the other groups 500 seconds after lidocaine addition (p < 0.05). Between the 5 and 2% lidocaine groups, 5% lidocaine showed a stronger vasodilatory effect 400 to 600 seconds after lidocaine addition (p < 0.01); however, there was no significant difference in these groups after 700 seconds. Additionally, there was no difference in the time required for the relaxation force to reach equilibrium among the 5, 2, and 1% lidocaine groups. Conclusion Although our study confirmed the dose-dependent vasodilatory effect of lidocaine, 5% lidocaine showed the best vasodilatory effect and continuity with minimal irreversible changes in the arterial tissue.

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42

Dalton, P. A., and M. J. Stokes. "Acoustic myography reflects force changes during dynamic concentric and eccentric contractions of the human biceps brachii muscle." European Journal of Applied Physiology and Occupational Physiology 63, no. 6 (1991): 412–16. http://dx.doi.org/10.1007/bf00868071.

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43

Bamani, Eran, Nadav D. Kahanowich, Inbar Ben-David, and Avishai Sintov. "Robust Multi-User In-Hand Object Recognition in Human-Robot Collaboration Using a Wearable Force-Myography Device." IEEE Robotics and Automation Letters 7, no. 1 (January 2022): 104–11. http://dx.doi.org/10.1109/lra.2021.3118087.

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44

Bian, K., and R. D. Bukoski. "Modulation of resistance artery force generation by extracellular Ca2+." American Journal of Physiology-Heart and Circulatory Physiology 269, no. 1 (July 1, 1995): H230—H238. http://dx.doi.org/10.1152/ajpheart.1995.269.1.h230.

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We tested the hypothesis that increasing extracellular Ca2+ (Cao) over a physiological concentration range depresses vascular smooth muscle force generation by altering the intracellular Ca2+ (Cai)-force relationship. Mesenteric resistance arteries were isolated from Wistar rats; Cai and isometric force were measured using a fura-based method and wire myography. Vessels were depleted of releasable Cai by repeated contraction with norepinephrine; Cao was then cumulatively added back from 0.025-2.5 mM in the presence of an agonist. With norepinephrine, serotonin, prostaglandin F2 alpha, and K+, Cao from 0.025 to 0.8 mM induced a graded increase in Cai and active stress. With the receptor agonists but not K+ raising Cao from 0.8 to 1.6 mM and from 1.6 to 2.5 mM decreased active stress to 82 +/- 6 and 54 +/- 6% of maximum, respectively, P < 0.05. Although there was a transient decrease in Cai in response to both 1.6 and 2.5 mM Cao, steady-state Cai only decreased significantly in response to 2.5 mM Cao (85 +/- 3% of maximum). Inhibition of the sarcoplasmic reticulum Ca(2+)-adenosinetriphosphatase with 1 microM thapsigargin had no effect on the decrease in force induced by high Ca2+. The decrease in active stress induced by 1.6 and 2.5 mM Cao was inhibited by Ca2+ channel antagonists and by blockade of Ca(2+)-activated K+ channels with charybdotoxin (with 1.6 mM Cao, control tension = 67 +/- 10% of maximum vs. charybdotoxin = 99.2 +/- 1%, P < 0.05; n = 9).(ABSTRACT TRUNCATED AT 250 WORDS)

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45

Stokes, M. J., and R. G. Cooper. "Muscle sounds during voluntary and stimulated contractions of the human adductor pollicis muscle." Journal of Applied Physiology 72, no. 5 (May 1, 1992): 1908–13. http://dx.doi.org/10.1152/jappl.1992.72.5.1908.

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The relationships between force, electromyography (EMG), and muscle sounds recorded by acoustic myography (AMG) were investigated for both voluntary and stimulated isometric contractions in the adductor pollicis muscle. Voluntary activity was performed at 10, 25, 50, 75, 85, and 100% of maximal voluntary contraction (MVC) force. Stimulated contractions were produced by supramaximal electrical stimulation of the ulnar nerve at the wrist at frequencies of 10, 20, 30, 50, 70, and 100 Hz. Contractions lasted for 4 s each, and were performed in random order with a 3-min rest between each. The voluntary and stimulation studies were performed in random order between subjects. Simultaneous recordings were obtained for force, force oscillation (from the differentiated force signal), and raw and integrated AMG (IAMG) and EMG (IEMG). During voluntary contractions, IAMG increased with force up to MVC (r2 = 0.99, P less than 0.001) in a curvilinear fashion and a similar relationship was seen between force and IEMG (r2 = 0.99, P less than 0.001). Conversely, during stimulated contractions as stimulation frequency increased, IAMG decreased in a fashion mirroring the frequency-force curve. The frequency of the AMG signal matched stimulation frequency and declines in total IAMG were due to reductions in amplitude of the AMG signal. The stimulation frequency-oscillation of force relationship was identical to that seen for stimulation frequency and IAMG. Integrated EMG increased linearly with stimulation frequency (r = 0.99). The stimulation results suggest that muscle sounds reflect oscillation of muscle fibers and that AMG signal characteristics are determined by motor control mechanisms rather than intrinsic contractile processes.

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Xiao, Zhen Gang, and Carlo Menon. "An Investigation on the Sampling Frequency of the Upper-Limb Force Myographic Signals." Sensors 19, no. 11 (May 28, 2019): 2432. http://dx.doi.org/10.3390/s19112432.

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Force myography (FMG) is an emerging method to register muscle activity of a limb using force sensors for human–machine interface and movement monitoring applications. Despite its newly gained popularity among researchers, many of its fundamental characteristics remain to be investigated. The aim of this study is to identify the minimum sampling frequency needed for recording upper-limb FMG signals without sacrificing signal integrity. Twelve healthy volunteers participated in an experiment in which they were instructed to perform rapid hand actions with FMG signals being recorded from the wrist and the bulk region of the forearm. The FMG signals were sampled at 1 kHz with a 16-bit resolution data acquisition device. We downsampled the signals with frequencies ranging from 1 Hz to 500 Hz to examine the discrepancies between the original signals and the downsampled ones. Based on the results, we suggest that FMG signals from the forearm and wrist should be collected with minimum sampling frequencies of 54 Hz and 58 Hz for deciphering isometric actions, and 70 Hz and 84 Hz for deciphering dynamic actions. This fundamental work provides insight into minimum requirements for sampling FMG signals such that the data content of such signals is not compromised.

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47

Li, Jia, Adam Pacheck, Benjamin Sanchez, and Seward B. Rutkove. "Single and modeled multifrequency electrical impedance myography parameters and their relationship to force production in the ALS SOD1G93A mouse." Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration 17, no. 5-6 (April 14, 2016): 397–403. http://dx.doi.org/10.3109/21678421.2016.1165258.

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Ishibashi, K., and R. D. Bukoski. "Myosin isoform expression and force generation in cultured resistance arteries." American Journal of Physiology-Cell Physiology 272, no. 4 (April 1, 1997): C1144—C1150. http://dx.doi.org/10.1152/ajpcell.1997.272.4.c1144.

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Organ culture of mesenteric resistance arteries results in a loss of force-generating ability, which is prevented by 1alpha,25-dihydroxyvitamin D3 [1,25(OH)2D3]. We have tested the hypothesis that the culture-induced decrease in active stress is associated with altered myosin isoform expression. Rat mesenteric resistance arteries were studied immediately (fresh) or after incubation at 37 degrees C for 48 h in culture medium (control), with 300 pg/ml 1,25(OH)2D3, or with 5 microg/ml insulin. Isometric force was measured by myography; myosin heavy chain (MHC) and regulatory myosin light chain isoform (MLC) contents were determined using sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Maximal active stress to 100 mM K+ (mN/mm2) was greater for fresh (147.8 +/- 4.9) than control (109.2 +/- 4.6, P = 0.001) or insulin (79.6 +/- 8.6, P < 0.001) but not 1,25(OH)2D3 (137.4 +/- 9.5, P = 0.197). Organ culture did not alter MLC or MHC smooth muscle (SM)-1 isoform content. MHC SM-2 content (nmol/mg protein) was greater in fresh (0.038 +/- 0.003) than control (0.026 +/- 0.003, P = 0.012) and insulin (0.027 +/- 0.002, P = 0.018) but not 1,25(OH)2D3 (0.036 +/- 0.003, P = 0.693); nonmuscle MHC (NMM) was observed in insulin. The maximal active stress response to K+ significantly correlated with SM-2 MHC isoform content (r2 = 0.483, P < 0.001). We conclude that 1) arterial organ culture alters MHC isoform content, 2) SM-2 MHC isoform content positively correlates with active stress generation, 3) 1,25(OH)2D3 maintains force-generating capacity by preventing the shift of MHC isoform expression, and 4) insulin impairs force-generating ability by lowering MHC SM-2 content and stimulating NMM expression.

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Ahmadizadeh, Chakaveh, Lukas-Karim Merhi, Brittany Pousett, Sohail Sangha, and Carlo Menon. "Toward Intuitive Prosthetic Control: Solving Common Issues Using Force Myography, Surface Electromyography, and Pattern Recognition in a Pilot Case Study." IEEE Robotics & Automation Magazine 24, no. 4 (December 2017): 102–11. http://dx.doi.org/10.1109/mra.2017.2747899.

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50

Liu, Chin-Hung, Mei-Fang Chen, Tzu-Ling Tseng, Lih-Geeng Chen, Jon-Son Kuo, and Tony Jer-Fu Lee. "Oroxylin A, but Not Vasopressin, Ameliorates Cardiac Dysfunction of Endotoxemic Rats." Evidence-Based Complementary and Alternative Medicine 2012 (2012): 1–12. http://dx.doi.org/10.1155/2012/408187.

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The mortality in septic patients with myocardial dysfunction is higher than those without it. Beneficial effects of flavonoid oroxylin A (Oro-A) on endotoxemic hearts were evaluated and compared with that of arginine vasopressin (AVP) which is used to reverse hypotension in septic patients. Endotoxemia in rats was induced by one-injection of lipopolysaccharides (LPS, 10 mg/kg, i.p.), and hearts were isolated 5-hrs or 16-hrs later. Isolated hearts with constant-pressure or constant-flow mode were examined by Langendorff technique. Rate and force of contractions of isolated atrial and ventricular strips were examined by tissue myography. Isolated endotoxemic hearts were characterized by decreased or increased coronary flow (CF) in LPS-treated-for-5hr and LPS-treated-for-16-hr groups, respectively, with decreased inotropy in both groups. Oro-A-perfusion ameliorated while AVP-perfusion worsened the decreased CF and inotropy in both preparations. Oro-A and AVP, however, did not affect diminished force or rate of contraction of atrial and ventricular strips of endotoxemic hearts. Oro-A-induced CF increase was not affected following coronary endothelium-denudation with saponin. These results suggest that Oro-A ameliorates LPS-depressed cardiac functions by increasing CF, leading to positive inotropy. In contrast, AVP aggravates cardiac dysfunction by decreasing CF. Oro-A is a potentially useful candidate for treating endotoxemia complicated with myocardial dysfunction.

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