Sonomyographic responses during voluntary isometric ramp contraction of the human rectus femoris muscle

Estimation of joint torque in dynamic activities using wearable A-mode ultrasound

The human body constantly experiences mechanical loading. However, quantifying internal loads within the musculoskeletal system remains challenging, especially during unconstrained dynamic activities. Conventional measures are constrained to laboratory settings, and existing wearable approaches lack muscle specificity or validation during dynamic movement. Here, we present a strategy for estimating corresponding joint torque from muscles with different architectures during various dynamic activities using wearable A-mode ultrasound. We first introduce a method to track changes in muscle thickness using single-element ultrasonic transducers. We then estimate elbow and knee torque with errors less than 7.6% and coefficients of determination (R2) greater than 0.92 during controlled isokinetic contractions. Finally, we demonstrate wearable joint torque estimation during dynamic real-world tasks, including weightlifting, cycling, and both treadmill and outdoor locomotion. The capability to assess joint torque during unconstrained real-world activities can provide new insights into muscle function and movement biomechanics, with potential applications in injury prevention and rehabilitation.

Multi-Sensing Techniques with Ultrasound for Musculoskeletal Assessment: A Review

The study of muscle contractions generated by the muscle-tendon unit (MTU) plays a critical role in medical diagnoses, monitoring, rehabilitation, and functional assessments, including the potential for movement prediction modeling used for prosthetic control. Over the last decade, the use of combined traditional techniques to quantify information about the muscle condition that is correlated to neuromuscular electrical activation and the generation of muscle force and vibration has grown. The purpose of this review is to guide the reader to relevant works in different applications of ultrasound imaging in combination with other techniques for the characterization of biological signals. Several research groups have been using multi-sensing systems to carry out specific studies in the health area. We can divide these studies into two categories: human-machine interface (HMI), in which sensors are used to capture critical information to control computerized prostheses and/or robotic actuators, and physiological study, where sensors are used to investigate a hypothesis and/or a clinical diagnosis. In addition, the relevance, challenges, and expectations for future work are discussed.

Toward Soft Wearable Strain Sensors for Muscle Activity Monitoring

The force-generating capacity of skeletal muscle is an important metric in the evaluation and diagnosis of musculoskeletal health. Measuring changes in muscle force exertion is essential for tracking the progress of athletes during training, for evaluating patients’ recovery after muscle injury, and also for assisting the diagnosis of conditions such as muscular dystrophy, multiple sclerosis, or Parkinson’s disease. Traditional hardware for strength evaluation requires technical training for operation, generates discrete time points for muscle assessment, and is implemented in controlled settings. The ability to continuously monitor muscle force without restricting the range of motion or adapting the exercise protocol to suit specific hardware would allow for a richer dataset that can help unlock critical features of muscle health and strength evaluation. In this paper, we employ wearable, ultra-sensitive soft strain sensors for tracking changes in muscle deformation during contractions. We demonstrate the sensors’ sensitivity to isometric contractions, as well as the sensors’ capacity to track changes in peak torque over the course of an isokinetic fatiguing protocol for the knee extensors. The wearable soft system was able to efficiently estimate peak joint torque reduction caused by muscle fatigue (mean NRMSE = 0.15±0.03).

Human skeletal muscle size with ultrasound imaging: a comprehensive review

Skeletal muscle size is an important factor in assessing adaptation to exercise training and detraining, athletic performance, age-associated atrophy and mobility decline, clinical conditions associated with cachexia, and overall skeletal muscle health. Magnetic resonance (MR) imaging and computed tomography (CT) are widely accepted as the gold standard methods for skeletal muscle size quantification. However, it is not always feasible to use these methods (e.g., field studies, bedside studies, large cohort studies). Ultrasound has been available for skeletal muscle examination for more than 50 years and the development, utility, and validity of ultrasound imaging are underappreciated. It is now possible to use ultrasound in situations where MR and CT imaging are not suitable. This review provides a comprehensive summary of ultrasound imaging and human skeletal muscle size assessment. Since the first study in 1968, more than 600 articles have used ultrasound to examine the cross-sectional area and/or volume of 107 different skeletal muscles in more than 27,500 subjects of various ages, health status, and fitness conditions. Data from these studies, supported by decades of technological developments, collectively show that ultrasonography is a valid tool for skeletal muscle size quantification. Considering the wide-ranging connections between human health and function and skeletal muscle mass, the utility of ultrasound imaging will allow it to be employed in research investigations and clinical practice in ways not previously appreciated or considered.

Electrical stimulator with mechanomyography-based real-time monitoring, muscle fatigue detection, and safety shut-off: a pilot study

Functional electrical stimulation (FES) has been used to produce force-related activities on the paralyzed muscle among spinal cord injury (SCI) individuals. Early muscle fatigue is an issue in all FES applications. If not properly monitored, overstimulation can occur, which can lead to muscle damage. A real-time mechanomyography (MMG)-based FES system was implemented on the quadriceps muscles of three individuals with SCI to generate an isometric force on both legs. Three threshold drop levels of MMG-root mean square (MMG-RMS) feature (thr50, thr60, and thr70; representing 50%, 60%, and 70% drop from initial MMG-RMS values, respectively) were used to terminate the stimulation session. The mean stimulation time increased when the MMG-RMS drop threshold increased (thr50: 22.7 s, thr60: 25.7 s, and thr70: 27.3 s), indicating longer sessions when lower performance drop was allowed. Moreover, at thr70, the torque dropped below 50% from the initial value in 14 trials, more than at thr50 and thr60. This is a clear indication of muscle fatigue detection using the MMG-RMS value. The stimulation time at thr70 was significantly longer (p = 0.013) than that at thr50. The results demonstrated that a real-time MMG-based FES monitoring system has the potential to prevent the onset of critical muscle fatigue in individuals with SCI in prolonged FES sessions.

Ultrasound Imaging as a Diagnostic Tool to Assess the Functional Status of Muscles after a Spinal Cord Injury

The aim of this study was to evaluate the use of ultrasound imaging (USI) as a diagnostic tool to assess muscle function after a spinal cord injury (SCI). Ultrasound videos of the gastrocnemius medialis muscle were recorded both at rest and during attempted maximum voluntary contraction (MVC) for fifteen participants with a SCI and fifteen able-bodied controls. Measurements were repeated at monthly intervals for participants in the SCI group during their inpatient stay. Differences in muscle echogenicity and thickness were detected between both able-bodied and SCI groups and subgroups of SCI participants, suggesting USI can detect and monitor changes in muscle structure which are characteristic of atrophy. Decreased muscle movement in the SCI groups was also detected during attempted MVC. The ability of USI to distinguish between different levels of function demonstrates the potential of USI as a quantitative tool to assess muscles.

Automatic Detection of Contracting Muscle Regions via the Deformation Field of Transverse Ultrasound Images: A Feasibility Study

Accurate identification of contracting muscles can help us to understand the muscle function in both physiological and pathological conditions. Conventional electromyography (EMG) have limited access to deep muscles, crosstalk, or instability in the recordings. Accordingly, a novel framework was developed to detect contracting muscle regions based on the deformation field of transverse ultrasound images. We first estimated the muscle movements in a stepwise calculation, to derive the deformation field. We then calculated the divergence of the deformation field to locate the expanding or shrinking regions during muscle contractions. Two preliminary experiments were performed to evaluate the feasibility of the developed algorithm. Using concurrent intramuscular EMG recordings, Experiment I verified that the divergence map can capture the activity of superficial and deep muscles, when muscles were activated voluntarily or through electrical stimulation. Experiment II verified that the divergence map can only capture contracting muscles but not muscle shortening during passive movements. The results demonstrated that the divergence can individually capture the activity of muscles at different depths, and was not sensitive to muscle shortening during passive movements. The proposed framework can automatically detect the regions of contracting muscle, and could potentially serve as a tool to assess the functions of a group of muscles concurrently.

Ultrasound Measurement of Skeletal Muscle Contractile Parameters Using Flexible and Wearable Single-Element Ultrasonic Sensor

Skeletal muscle is considered as a near-constant volume system, and the contractions of the muscle are related to the changes in tissue thickness. Assessment of the skeletal muscle contractile parameters such as maximum contraction thickness (Th), contraction time (Tc), contraction velocity (Vc), sustain time (Ts), and half-relaxation (Tr) provides valuable information for various medical applications. This paper presents a single-element wearable ultrasonic sensor (WUS) and a method to measure the skeletal muscle contractile parameters in A-mode ultrasonic data acquisition. The developed WUS was made of double-layer polyvinylidene fluoride (PVDF) piezoelectric polymer films with a simple and low-cost fabrication process. A flexible, lightweight, thin, and small size WUS would provide a secure attachment to the skin surface without affecting the muscle contraction dynamics of interest. The developed WUS was employed to monitor the contractions of gastrocnemius (GC) muscle of a human subject. The GC muscle contractions were evoked by the electrical muscle stimulation (EMS) at varying EMS frequencies from 2 Hz up to 30 Hz. The tissue thickness changes due to the muscle contractions were measured by utilizing a time-of-flight method in the ultrasonic through-transmission mode. The developed WUS demonstrated the capability to monitor the tissue thickness changes during the unfused and fused tetanic contractions. The tetanic progression level was quantitatively assessed using the parameter of the fusion index (FI) obtained. In addition, the contractile parameters (Th, Tc, Vc, Ts, and Tr) were successfully extracted from the measured tissue thickness changes. In addition, the unfused and fused tetanus frequencies were estimated from the obtained FI-EMS frequency curve. The WUS and ultrasonic method proposed in this study could be a valuable tool for inexpensive, non-invasive, and continuous monitoring of the skeletal muscle contractile properties.

Automatic Tracking of Muscle Cross-Sectional Area Using Convolutional Neural Networks with Ultrasound

OBJECTIVES

The purpose of this study was to develop an automatic tracking method for the muscle cross-sectional area (CSA) on ultrasound (US) images using a convolutional neural network (CNN). The performance of the proposed method was evaluated and compared with that of the state-of-the art muscle segmentation method.

METHODS

A real-time US image sequence was obtained from the rectus femoris muscle during voluntary contraction. A CNN was built to segment the rectus femoris muscle and calculate the CSA in each US frame. This network consisted of 2 stages: feature extraction and score map reconstruction. The training of the network was divided into 3 steps with output score map resolutions of one-fourth, one-half, and all of the original image. We evaluated the segmentation performance of our method with 5-fold cross-validation. The mean precision, recall, and dice similarity score were calculated.

RESULTS

The mean precision, recall, and Dice's coefficient (DSC) ± SD were 0.936 ± 0.029, 0.882 ± 0.045, and 0.907 ± 0.023, respectively. Compared with the state-of-the-art muscle segmentation method (constrained mutual-information-based free-form deformation), the proposed method using CNN showed high performance.

CONCLUSIONS

The automated method proposed in this study provides an accurate and efficient approach to the estimation of the muscle CSA during muscle contraction.

Automatic Muscle Fiber Orientation Tracking in Ultrasound Images Using a New Adaptive Fading Bayesian Kalman Smoother

This paper proposes a new algorithm for automatic estimation of muscle fiber orientation (MFO) in musculoskeletal ultrasound images, which is commonly used for both diagnosis and rehabilitation assessment of patients. The algorithm is based on a novel adaptive fading Bayesian Kalman filter (AF-BKF) and an automatic region of interest (ROI) extraction method. The ROI is first enhanced by the Gabor filter (GF) and extracted automatically using the revoting constrained Radon transform (RCRT) approach. The dominant MFO in the ROI is then detected by the RT and tracked by the proposed AF-BKF, which employs simplified Gaussian mixtures to approximate the non-Gaussian state densities and a new adaptive fading method to update the mixture parameters. An AF-BK smoother (AF-BKS) is also proposed by extending the AF-BKF using the concept of Rauch-Tung-Striebel smoother for further smoothing the fascicle orientations. The experimental results and comparisons show that: 1) the maximum segmentation error of the proposed RCRT is below nine pixels, which is sufficiently small for MFO tracking; 2) the accuracy of MFO gauged by RT in the ROI enhanced by the GF is comparable to that of using multiscale vessel enhancement filter-based method and better than those of local RT and revoting Hough transform approaches; and 3) the proposed AF-BKS algorithm outperforms the other tested approaches and achieves a performance close to those obtained by experienced operators (the overall covariance obtained by the AF-BKS is 3.19, which is rather close to that of the operators, 2.86). It, thus, serves as a valuable tool for automatic estimation of fascicle orientations and possibly for other applications in musculoskeletal ultrasound images.

In Vivo Flattening of the Central Aponeurosis of the Rectus Femoris Due to Knee Extension Torque in Healthy Young and Elderly Individuals With Knee Osteoarthritis

ABSTRACT

We aimed to elucidate the relationship between active force production and the curvature of the central aponeurosis (CA) of the rectus femoris in young healthy participants as fundamental data and compare the muscle CA curvature before and after straight leg raising (SLR) training in participants with knee osteoarthritis (OA). Central aponeurosis curvature was determined during submaximal and maximal voluntary contractions (MVCs) using ultrasonography. Twenty-five young healthy female volunteers underwent ultrasonographic measurements under conditions of isometric MVC. They were divided into a flat shaped CA group (flat) and an incompletely flat shaped CA group (remnant). Central aponeurosis curvature was calculated as the ratio of CA height and length in the axial view. Central aponeurosis shape and muscular strength before and after muscle training were measured in 11 participants with knee OA. In the young healthy individuals, maximal voluntary torque and changes in CA curvature were significantly higher in the flat group than in the remnant group (2.15 Nm/kg and - 17.7% vs 1.75 Nm/kg and -9.8%, respectively; P = 0.005). The rate of change of the CA curvature during contraction was significantly correlated with maximal voluntary torque corrected for body mass (r = 0.512). The CA curvature progressively decreased as %MVC increased. In the OA group, CA curvature during MVC after SLR training was significantly lower than that before SLR training (3.2% vs 7.2%; P = 0.031). Central aponeurosis curvature was associated with muscle strength, and the results supported our hypothesis that geometric observation of CA changes during contractions may reflect muscle fiber function. We aim to develop a new ultrasonographic skeletal muscle evaluation method based on our present findings.

Ultrasonic Measurement of Dynamic Muscle Behavior for Poststroke Hemiparetic Gait

Quantitative evaluation of the hemiparesis status for a poststroke patient is still challenging. This study aims to measure and investigate the dynamic muscle behavior in poststroke hemiparetic gait using ultrasonography. Twelve hemiparetic patients walked on a treadmill, and EMG, joint angle, and ultrasonography were simultaneously recorded for the gastrocnemius medialis muscle. Pennation angle was automatically extracted from ultrasonography using a tracking algorithm reported previously. The characteristics of EMG, joint angle, and pennation angle in gait cycle were calculated for both (affected and unaffected) sides of lower limbs. The results suggest that pennation angle could work as an important morphological index to continuous muscle contraction. The change pattern of pennation angle between the affected and unaffected sides is different from that of EMG. These findings indicate that morphological parameter extracted from ultrasonography can provide different information from that provided by EMG for hemiparetic gait.

Automatic Extraction of Central Tendon of Rectus Femoris (CT-RF) in Ultrasound Images Using a New Intensity-Compensated Free-Form Deformation-Based Tracking Algorithm With Local Shape Refinement

Ultrasonography is an important diagnostic imaging technique for visualization of tendons, which provides useful health diagnostic and fundamental information in neuromuscular studies of human motion systems. Conventional ultrasonic-based tendon studies, however, are highly dependent on subjective experience of operators due to various impairments of ultrasound images. Dynamic changes of muscle and tendon deformation in a sequence can hardly be manually processed. Consequently, there is an urgent need for automatic analysis of tendon behavior. This paper proposes an automatic ultrasonic tendon tracking algorithm to extract the shape deformation of central tendon of rectus femoris (CT-RF) from ultrasonic image sequences. The tracking problem is complicated by the highly deformable tendon, time-varying brightness, and the inconspicuousness of the target. To address this difficult tracking problem, we proposed a new intensity-compensated free-form deformation (IC-FFD)-based tracking algorithm with local shape refinement (LSR). Experimental results and comparison show that the proposed IC-FFD-LSR algorithm outperforms IC-FFD and conventional methods such as MI-FFD in CT-RF tracking.

An attempt to bridge muscle architecture dynamics and its instantaneous rate of force development using ultrasonography

Muscle force output is an essential index in rehabilitation assessment or physical exams, and could provide considerable insights for various applications such as load monitoring and muscle assessment in sports science or rehabilitation therapy. Besides direct measurement of force output using a dynamometer, electromyography has earlier been used in several studies to quantify muscle force as an indirect means. However, its spatial resolution is easily compromised as a summation of the action potentials from neighboring motor units of electrode site. To explore an alternative method to indirectly estimate the muscle force output, and with better muscle specificity, we started with an investigation on the relationship between architecture dynamics and force output of triceps surae. The muscular architecture dynamics is captured in ultrasonography sequences and estimated using a previously reported motion estimation method. Then an indicator named as the dorsoventrally averaged motion profile (DAMP) is employed. The performance of force output is represented by an instantaneous version of the rate of force development (RFD), namely I-RFD. From experimental results on ten normal subjects, there were significant correlations between the I-RFD and DAMP for triceps surae, both normalized between 0 and 1, with the sum of squares error at 0.0516±0.0224, R-square at 0.7929±0.0931 and root mean squared error at 0.0159±0.0033. The statistical significance results were less than 0.01. The present study suggested that muscle architecture dynamics extracted from ultrasonography during contraction is well correlated to the I-RFD and it can be a promising option for indirect estimation of muscle force output.

A novel outlier detection method for identifying torque-related transient patterns of in vivo muscle behavior

This paper proposed a novel outlier detection method, named l1-regularized outlier isolation and regression (LOIRE), to examine torque-related transient patterns of in vivo muscle behavior from multimodal signals, including electromyography (EMG), mechanomyography (MMG) and ultrasonography (US), during isometric muscle contraction. Eight subjects performed isometric ramp contraction of knee up to 90% of the maximal voluntary contraction, and EMG, MMG and US were simultaneously recorded from the rectus femoris muscle. Five features, including two root mean square amplitudes from EMG and MMG, muscle cross sectional area, muscle thickness and width from US were extracted. Then, local polynomial regression was used to obtain the signal-to-torque relationships and their derivatives. By assuming the signal-to-torque functions are basically quadratic, the LOIRE method is applied to identify transient torque-related patterns of EMG, MMG and US features as outliers of the linear derivative-to-torque functions. The results show that the LOIRE method can effectively reveal transient patterns in the signal-to-torque relationships (for example, sudden changes around 20% MVC can be observed from all features), providing important information about in vivo muscle behavior.

Estimation and visualization of longitudinal muscle motion using ultrasonography: a feasibility study

Ultrasonography is a convenient and widely used technique to look into the longitudinal muscle motion as it is radiation-free and real-time. The motion of localized parts of the muscle, disclosed by ultrasonography, spatially reflects contraction activities of the corresponding muscles. However, little attention was paid to the estimation of longitudinal muscle motion, especially towards estimation of dense deformation field at different depths under the skin. Yet fewer studies on the visualization of such muscle motion or further clinical applications were reported in the literature. A primal-dual algorithm was used to estimate the motion of gastrocnemius muscle (GM) in longitudinal direction in this study. To provide insights into the rules of longitudinal muscle motion, we proposed a novel framework including motion estimation, visualization and quantitative analysis to interpret synchronous activities of collaborating muscles with spatial details. The proposed methods were evaluated on ultrasound image sequences, captured at a rate of 25 frames per second from eight healthy subjects. In order to estimate and visualize the GM motion in longitudinal direction, each subject was asked to perform isometric plantar flexion twice. Preliminary results show that the proposed visualization methods provide both spatial and temporal details and they are helpful to study muscle contractions. One of the proposed quantitative measures was also tested on a patient with unilateral limb dysfunction caused by cerebral infarction. The measure revealed distinct patterns between the normal and the dysfunctional lower limb. The proposed framework and its associated quantitative measures could potentially be used to complement electromyography (EMG) and torque signals in functional assessment of skeletal muscles.

Relationship of EMG/SMG features and muscle strength level: an exploratory study on tibialis anterior muscles during plantar-flexion among hemiplegia patients

BACKGROUND

Improvement in muscle strength is an important aim for the rehabilitation of hemiplegia patients. Presently, the rehabilitation prescription depends on the evaluation results of muscle strength, which are routinely estimated by experienced physicians and therefore not finely quantitative. Widely-used quantification methods for disability, such as Barthel Index (BI) and motor component of Functional Independent Measure (M-FIM), yet have limitations in their application, since both of them differentiated disability better in lower than higher disability, and they are subjective and recorded in wide scales. In this paper, to explore finely quantitative measures for evaluation of muscle strength level (MSL), we start with the study on quantified electromyography (EMG) and sonomyography (SMG) features of tibialis anterior (TA) muscles among hemiplegia patients.

METHODS

12 hemiplegia subjects volunteered to perform several sets of plantar-flexion movements in the study, and their EMG signals and SMG signals were recorded on TA independently to avoid interference. EMG data were filtered and then the root-mean-square (RMS) was computed. SMG signals, specifically speaking, the muscle thickness of TA, were manually measured by two experienced operators using ultrasonography. Reproducibility of the SMG assessment on TA between operators was evaluated by non-parametric test (independent sample T test). Possible relationship between muscle thickness changes (TC) of TA and muscle strength level of hemiplegia patients was estimated.

RESULTS

Mean of EMG RMS between subjects is found linearly correlated with MSL (R2 = 0.903). And mean of TA muscle TC amplitudes is also linearly correlated with MSL among dysfunctional legs (R2 = 0.949). Moreover, rectified TC amplitudes (dysfunctional leg/ healthy leg, DLHL) and rectified EMG signals (DLHL) are found in linear correlation with MSL, with R2 = 0.756 and R2 = 0.676 respectively. Meanwhile, the preliminary results demonstrate that patients' peak values of TC are generally proportional to their personal EMG peak values in 12 dysfunctional legs and 12 healthy legs (R2 = 0.521).

CONCLUSIONS

It's concluded that SMG could be a promising option to quantitatively estimate MSL for hemiplegia patients during rehabilitation besides EMG. However, after this exploratory study, they should be further investigated on a larger number of subjects.

An indirect method to estimate the force output of triceps surae muscle

Estimation of force output generated by human muscle is an essential routine of clinical rehabilitation assessment, and could provide considerable insight into rehabilitation, motor control and robotics. Indirect methods for the estimation of force output could be helpful when a bulky and expensive dynamometer is not on hand. Electromyography has been used in previous studies to quantify it in the literature. However, the force output is a summation of the motor unit action potentials, and thus the contributions and performances of superficial and deep-lying muscles could hardly be separated from each other. In this preliminary study, we applied ultrasonography (US) to explore the feasibility of estimating triceps surae force output during isometric plantar flexion with spatial resolution from superficial to deeper muscles. The local deformations of US images are extracted to represent the morphological changes during force generation. It was found US could be utilized to decently (coefficient of determination at 0.875 ± 0.051 and normalized root mean square error 0.160 ± 0.035) estimate the force output and the measured force by a dynamometer.

Use of optical flow to estimate continuous changes in muscle thickness from ultrasound image sequences

Muscle thickness is one of the most widely used parameters for quantifying muscle function. Ultrasonography is frequently used to estimate changes in muscle thickness in both static and dynamic contractions. Conventionally, most such measurements are conducted by manual analysis of ultrasound images. This manual approach is time consuming, subjective, susceptible to error and not suitable for measuring dynamic change. In this study, we developed an automated tracking method based on an optical flow algorithm using an affine motion model. The goal of the study was to evaluate the performance of the proposed method by comparing it with the manual approach and by determining its repeatability. Real-time B-mode ultrasound was used to examine the rectus femoris during voluntary contraction. The coefficient of multiple correlation (CMC) was used to quantify the level of agreement between the two methods and the repeatability of the proposed method. The two methods were also compared by linear regression and Bland-Altman analysis. The findings indicated that the results obtained using the proposed method were in good agreement with those obtained using the manual approach (CMC = 0.97 ± 0.02, difference = -0.06 ± 0.22 mm) and were highly repeatable (CMC = 0.91 ± 0.07). In conclusion, the automated method proposed here provides an accurate, highly repeatable and efficient approach to the estimation of muscle thickness during muscle contraction.

Pre-processing for muscle motion analysis: adaptive guided image filtering for speckle reduction of ultrasound images

Skeletal muscle is an important tissue of human body, and its contractions control and regulate body motions. Muscle contraction results in morphological changes of the related muscles. Ultrasound imaging is an effective tool for studying muscle architectures and monitoring the morphological changes of muscles. The latter process can be realized with a motion estimation algorithm. However, ultrasound images are usually corrupted by speckle noises and performance of motion estimation methods can be significantly affected by the noises. To get a better performance in motion analysis, in this paper, as a pre-processing step, an adaptive filter named adaptive guided image filtering (AGF) is suggested to reduce speckle noises. We first transformed the multiplicative noise model into an additive one by taking the logarithm of the original speckled data, then performed AGF to obtain the filtered image, and finally took the tackled image back into exponent. Experimental results showed that AGF had a better performance in terms of noise attenuation and edge preservation compared with other standard filters. In quantitative results, the filtered images also had the highest Peak-Signal-to-Noise Ratio (PSNR) using AGF. It's believed that AGF is a good choice for the pre-processing stage of muscle motion analysis.

Continuous detection of muscle aspect ratio using keypoint tracking in ultrasonography

Muscle aspect ratio of cross-sectional area is one of the most widely used parameters for quantifying muscle function in both diagnosis and rehabilitation assessment. Ultrasound imaging has been frequently used to noninvasively study the characteristics of human muscles as a reliable method. However, the aspect ratio measurement is traditionally conducted by the manual digitization of reference points; thus, it is subjective, time-consuming, and prone to errors. In this paper, a novel method is proposed to continuously detect the muscle aspect ratio. Two keypoint pairs are manually digitized on the lateral and longitudinal borders at the first frame, and automatically tracked by an optical flow technique at the subsequent frames. The muscle aspect ratio is thereby obtained based on the estimated muscle width and thickness. Six ultrasound sequences from different subjects are used to evaluate this method, and the overall coefficient of multiple correlation of the results between manual and proposed methods is 0.97 ± 0.02. The linear regression shows that a good linear correlation between the results of the two methods is obtained (R(2) = 0.974), with difference -0.01 ± 0.16. The method proposed here provides an accurate, high repeatable, and efficient approach for estimating muscle aspect ratio during human motion, thus justifying its application in biological sciences.

Mechanomyogram for muscle function assessment: a review

BACKGROUND

Mechanomyography (MMG) has been extensively applied in clinical and experimental practice to examine muscle characteristics including muscle function (MF), prosthesis and/or switch control, signal processing, physiological exercise, and medical rehabilitation. Despite several existing MMG studies of MF, there has not yet been a review of these. This study aimed to determine the current status on the use of MMG in measuring the conditions of MFs.

METHODOLOGY/PRINCIPAL FINDINGS

Five electronic databases were extensively searched for potentially eligible studies published between 2003 and 2012. Two authors independently assessed selected articles using an MS-Word based form created for this review. Several domains (name of muscle, study type, sensor type, subject's types, muscle contraction, measured parameters, frequency range, hardware and software, signal processing and statistical analysis, results, applications, authors' conclusions and recommendations for future work) were extracted for further analysis. From a total of 2184 citations 119 were selected for full-text evaluation and 36 studies of MFs were identified. The systematic results find sufficient evidence that MMG may be used for assessing muscle fatigue, strength, and balance. This review also provides reason to believe that MMG may be used to examine muscle actions during movements and for monitoring muscle activities under various types of exercise paradigms.

CONCLUSIONS/SIGNIFICANCE

Overall judging from the increasing number of articles in recent years, this review reports sufficient evidence that MMG is increasingly being used in different aspects of MF. Thus, MMG may be applied as a useful tool to examine diverse conditions of muscle activity. However, the existing studies which examined MMG for MFs were confined to a small sample size of healthy population. Therefore, future work is needed to investigate MMG, in examining MFs between a sufficient number of healthy subjects and neuromuscular patients.