A comparison between mechanomyographic condenser microphone and accelerometer measurements during submaximal isometric, concentric and eccentric contractions

Phonomyography on Perioperative Neuromuscular Monitoring: An Overview

Complications related to neuromuscular blockade (NMB) could occur during anesthesia induction, maintenance, and emergency. It is recommended that neuromuscular monitoring techniques be utilized perioperatively to avoid adverse outcomes. However, current neuromuscular monitoring methods possess different shortcomings. They are cumbersome to use, susceptible to disturbances, and have limited alternative monitoring sites. Phonomyography (PMG) monitoring based on the acoustic signals yielded by skeletal muscle contraction is emerging as an interesting and innovative method. This technique is characterized by its convenience, stable signal quality, and multimuscle recording ability and shows great potential in the application field. This review summarizes the progression of PMG on perioperative neuromuscular monitoring chronologically and presents the merits, demerits, and challenges of PMG-based equipment, aiming at underscoring the potential of PMG-based apparatuses for neuromuscular monitoring.

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.

Comparing electro- and mechano-myographic muscle activation patterns in self-paced pediatric gait

Electromyography (EMG) is the standard modality for measuring muscle activity. However, the convenience and availability of low-cost accelerometer-based wearables makes mechanomyography (MMG) an increasingly attractive alternative modality for clinical applications. Literature to date has demonstrated a strong association between EMG and MMG temporal alignment in isometric and isokinetic contractions. However, the EMG-MMG relationship has not been studied in gait. In this study, the concurrence of EMG- and MMG-detected contractions in the tibialis anterior, lateral gastrocnemius, vastus lateralis, and biceps femoris muscles were investigated in children during self-paced gait. Furthermore, the distribution of signal power over the gait cycle was statistically compared between EMG-MMG modalities. With EMG as the reference, muscular contractions were detected based on MMG with balanced accuracies between 88 and 94% for all muscles except the gastrocnemius. MMG signal power differed from that of EMG during certain phases of the gait cycle in all muscles except the biceps femoris. These timing and power distribution differences between the two modalities may in part be related to muscle fascicle length changes that are unique to muscle motion during gait. Our findings suggest that the relationship between EMG and MMG appears to be more complex during gait than in isometric and isokinetic contractions.

A Feasibility Study to Assess Vibration and Sound From Zygapophyseal Joints During Motion Before and After Spinal Manipulation

OBJECTIVE

This feasibility study used novel accelerometry (vibration) and microphone (sound) methods to assess crepitus originating from the lumbar spine before and after side-posture spinal manipulative therapy (SMT).

METHODS

This study included 5 healthy and 5 low back pain (LBP) participants. Nine accelerometers and 1 specialized directional microphone were applied to the lumbar region, allowing assessment of crepitus. Each participant underwent full lumbar ranges of motion (ROM), bilateral lumbar SMT, and repeated full ROM. After full ROMs the participants received side-posture lumbar SMT on both sides by a licensed doctor of chiropractic. Accelerometer and microphone recordings were made during all pre- and post-SMT ROMs. Primary outcome was a descriptive report of crepitus prevalence (average number of crepitus events/participant). Participants were also divided into 3 age groups for comparisons (18-25, 26-45, and 46-65 years).

RESULTS

Overall, crepitus prevalence decreased pre-post SMT (average pre = 1.4 crepitus/participant vs post = 0.9). Prevalence progressively increased from the youngest to oldest age groups (pre-SMT = 0.0, 1.67, and 2.0, respectively; and post-SMT = 0.5, 0.83, and 1.5). Prevalence was higher in LBP participants compared with healthy (pre-SMT-LBP = 2.0, vs pre-SMT-healthy = 0.8; post-SMT-LBP = 1.0 vs post-SMT-healthy = 0.8), even though healthy participants were older than LBP participants (40.8 years vs 27.8 years); accounting for age: pre-SMT-LBP = 2.0 vs pre-SMT-healthy = 0.0; post-SMT-LBP = 1.0 vs post-SMT-healthy = 0.3.

CONCLUSIONS

Our findings indicated that a larger study is feasible. Other findings included that crepitus prevalence increased with age, was higher in participants with LBP than in healthy participants, and overall decreased after SMT. This study indicated that crepitus assessment using accelerometers has the potential of being an outcome measure or biomarker for assessing spinal joint (facet/zygapophyseal joint) function during movement and the effects of LBP treatments (eg, SMT) on zygapophyseal joint function.

System identification of velocity mechanomyogram measured with a capacitor microphone for muscle stiffness estimation

A mechanomyogram (MMG) measured with a displacement sensor (displacement MMG) can provide a better estimation of longitudinal muscle stiffness than that measured with an acceleration sensor (acceleration MMG), but the displacement MMG cannot provide transverse muscle stiffness. We propose a method to estimate both longitudinal and transverse muscle stiffness from a velocity MMG using a system identification technique. The aims of this study are to show the advantages of the proposed method. The velocity MMG was measured using a capacitor microphone and a differential circuit, and the MMG, evoked by electrical stimulation, of the tibialis anterior muscle was measured five times in seven healthy young male volunteers. The evoked MMG system was identified using the singular value decomposition method and was approximated with a fourth-order model, which provides two undamped natural frequencies corresponding to the longitudinal and transverse muscle stiffness. The fluctuation of the undamped natural frequencies estimated from the velocity MMG was significantly smaller than that from the acceleration MMG. There was no significant difference between the fluctuations of the undamped natural frequencies estimated from the velocity MMG and that from the displacement MMG. The proposed method using the velocity MMG is thus more advantageous for muscle stiffness estimation.

Muscle stiffness estimation using a system identification technique applied to evoked mechanomyogram during cycling exercise

The aims of this study were to develop a method to extract the evoked mechanomyogram (MMG) during cycling exercise and to clarify muscle stiffness at various cadences, workloads, and power. Ten young healthy male participants were instructed to pedal a cycle ergometer at cadences of 40 and 60 rpm. The loads were 4.9, 9.8, 14.7, and 19.6 N, respectively. One electrical stimulus per two pedal rotations was applied to the vastus lateralis muscle at a knee angle of 80° in the down phase. MMGs were measured using a capacitor microphone, and the MMGs were divided into stimulated and non-stimulated sequences. Each sequence was synchronously averaged. The synchronously averaged non-stimulated MMG was subtracted from the synchronously averaged stimulated MMG to extract an evoked MMG. The evoked MMG system was identified and the poles of the transfer function were calculated. The poles and mass of the vastus lateralis muscle were used to estimate muscle stiffness. Results showed that muscle stiffness was 186-626 N /m and proportional to the workloads and power. In conclusion, our method can be used to assess muscle stiffness proportional to the workload and power.

MEASUREMENT AND ESTIMATION OF MUSCLE CONTRACTION STRENGTH USING MECHANOMYOGRAPHY BASED ON ARTIFICIAL NEURAL NETWORK ALGORITHM

Muscle contraction strength estimation using mechanomyographic (MMG) signal is typically calculated by the root mean square (RMS) amplitude. Raw MMG signal is processed by rectification, low-pass filtering, and mapping. In this work, beside RMS amplitude, another significant parameter of MMG signal, i.e. frequency variance (VAR), is introduced and used for constructing an algorithm for estimating the muscle contraction strength. Seven participants produced isometric contractions about the elbow while MMG signal and generated torque (resultant of muscle contraction strength) of biceps brachii were recorded. We found that MMG RMS increased monotonously and VAR decreased under incremental voluntary contractions. Based on these results, a two-layer neural network was utilized for the model of estimating the muscle contraction strength from MMG RMS and VAR. Experimental evaluation was performed under constant posture and sinusoidal contractions at 0.5 Hz, 0.25 Hz, 0.125 Hz, and random frequency. The results of the proposed algorithm and MMG RMS linear mapping were also compared. The proposed algorithm has better accuracy than linear mapping for all contraction frequencies. The mean absolute error decreased 6% for the 0.5Hz contraction, 43% for 0.25 Hz contraction, 52% for 0.125 Hz contraction, and 30% for random frequency contraction.

Propagation direction of natural mechanical oscillations in the biceps brachii muscle during voluntary contraction

The aim of the study was to determine the directionality of the coupling of mechanical vibrations across the biceps brachii muscle at different frequencies of interest during voluntary contraction. The vibrations that are naturally generated by skeletal muscles were recorded by a two-dimensional array of skin mounted accelerometers over the biceps brachii muscle (surface mechanomyogram, S-MMG) during voluntary isometric contractions in ten healthy young men. As a measure of the similarity of vibration between a given pair of accelerometers, the spatial coherence of S-MMG at low (f<25Hz) and high (f>25Hz) frequency bands were investigated to determine if the coupling of the natural mechanical vibrations were due to the different physiological muscle activity at low and high frequencies. In both frequency bands, spatial coherence values for sensor pairs aligned longitudinally along the proximal to distal ends of the biceps were significantly higher compared with those for the sensor pairs oriented perpendicular to the muscle fibers. This difference was more evident at the higher frequency band. The findings indicated that coherent mechanical oscillations mainly propagated along the longitudinal direction of the biceps brachii muscle fibers at high frequencies (f>25Hz).

A review of non-invasive techniques to detect and predict localised muscle fatigue

Muscle fatigue is an established area of research and various types of muscle fatigue have been investigated in order to fully understand the condition. This paper gives an overview of the various non-invasive techniques available for use in automated fatigue detection, such as mechanomyography, electromyography, near-infrared spectroscopy and ultrasound for both isometric and non-isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who wish to select the most appropriate methodology for research on muscle fatigue detection or prediction, or for the development of devices that can be used in, e.g., sports scenarios to improve performance or prevent injury. To date, research on localised muscle fatigue focuses mainly on the clinical side. There is very little research carried out on the implementation of detecting/predicting fatigue using an autonomous system, although recent research on automating the process of localised muscle fatigue detection/prediction shows promising results.

On functional motor adaptations: from the quantification of motor strategies to the prevention of musculoskeletal disorders in the neck-shoulder region

BACKGROUND

Occupations characterized by a static low load and by repetitive actions show a high prevalence of work-related musculoskeletal disorders (WMSD) in the neck-shoulder region. Moreover, muscle fatigue and discomfort are reported to play a relevant initiating role in WMSD.

AIMS

To investigate relationships between altered sensory information, i.e. localized muscle fatigue, discomfort and pain and their associations to changes in motor control patterns.

MATERIALS & METHODS

In total 101 subjects participated. Questionnaires, subjective assessments of perceived exertion and pain intensity as well as surface electromyography (SEMG), mechanomyography (MMG), force and kinematics recordings were performed.

RESULTS

Multi-channel SEMG and MMG revealed that the degree of heterogeneity of the trapezius muscle activation increased with fatigue. Further, the spatial organization of trapezius muscle activity changed in a dynamic manner during sustained contraction with acute experimental pain. A graduation of the motor changes in relation to the pain stage (acute, subchronic and chronic) and work experience were also found. The duration of the work task was shorter in presence of acute and chronic pain. Acute pain resulted in decreased activity of the painful muscle while in subchronic and chronic pain, a more static muscle activation was found. Posture and movement changed in the presence of neck-shoulder pain. Larger and smaller sizes of arm and trunk movement variability were respectively found in acute pain and subchronic/chronic pain. The size and structure of kinematics variability decreased also in the region of discomfort. Motor variability was higher in workers with high experience. Moreover, the pattern of activation of the upper trapezius muscle changed when receiving SEMG/MMG biofeedback during computer work.

DISCUSSION

SEMG and MMG changes underlie functional mechanisms for the maintenance of force during fatiguing contraction and acute pain that may lead to the widespread pain seen in WMSD. A lack of harmonious muscle recruitment/derecruitment may play a role in pain transition. Motor behavior changed in shoulder pain conditions underlining that motor variability may play a role in the WMSD development as corroborated by the changes in kinematics variability seen with discomfort. This prognostic hypothesis was further, supported by the increased motor variability among workers with high experience.

CONCLUSION

Quantitative assessments of the functional motor adaptations can be a way to benchmark the pain status and help to indentify signs indicating WMSD development. Motor variability is an important characteristic in ergonomic situations. Future studies will investigate the potential benefit of inducing motor variability in occupational settings.

Recognition of forearm muscle activity by continuous classification of multi-site mechanomyogram signals

Recent studies on identifying multiple activation states from mechanomyogram (MMG) signals for the purpose of controlling switching interfaces have employed pattern recognition methods where MMG signal features from multiple muscle sites are extracted and classified. The purpose of this study is to determine if MMG signal features retain enough discriminatory information to allow reliable continuous classification, and to determine if there is a decline in classification accuracy over short time periods. MMG signals were recorded from two accelerometers attached to the flexor carpi radialis and extensor carpi radialis muscles of 12 able-bodied participants as participants performed three classes of forearm muscle activity. The data were collected over five recording sessions, with a ten-minute interval between each session. The data were spliced into 256 ms epochs, and a comprehensive set of signal features was extracted. A pattern classifier, trained with continuously acquired signal features from the first recording session, was tested with signals recorded from the other sessions. The average classification accuracy over the five sessions was 89 ± 2%. There was no obvious declining trend in classification accuracy with time. These results show that MMG signals recorded at the forearm retain enough discriminatory information to allow continuous recognition of hand motion across multiple (>90) repetitions, and the MMG-classifier does not show short-term degradation. These results indicate the potential of MMG as a multifunction control signal for muscle-machine interfaces.

The image of motor units architecture in the mechanomyographic signal during the single motor unit contraction: in vivo and simulation study

The mechanomyographic (MMG) signal analysis has been performed during single motor unit (MU) contractions of the rat medial gastrocnemius muscle. The MMG has been recorded as a muscle surface displacement by using a laser distance sensor. The profiles of the MMG signal let to categorize these signals for particular MUs into three classes. Class MMG-P (positive) comprises MUs with the MMG signal similar to the force signal profile, where the distance between the muscle surface and the laser sensor increases with the force increase. The class MMG-N (negative) has also the MMG profile similar to the force profile, however the MMG is inverted in comparison to the force signal and the distance measured by using laser sensor decreases with the force increase. The third class MMG-M (mixed) characterize the MMG which initially increases with the force increases and when the force exceeds some level it starts to decrease towards the negative values. The semi-pennate muscle model has been proposed, enabling estimation of the MMG generated by a single MU depending on its localization. The analysis have shown that in the semi-pennate muscle the localization of the MU and the relative position of the laser distance sensor determine the MMG profile and amplitude. Thus, proposed classification of the MMG recordings is not related to the physiological types of MUs, but only to the MU localization and mentioned sensor position. When the distance sensor is located over the middle of the muscle belly, a part of the muscle fibers have endings near the location of the sensor beam. For the MU MMG of class MMG-N the deflection of the muscle surface proximal to the sensor mainly influences the MMG recording, whereas for the MU MMG class MMG-P, it is mainly the distal muscle surface deformation. For the MU MMG of MMG-M type the effects of deformation within the proximal and distal muscle surfaces overlap. The model has been verified with experimental recordings, and its responses are consistent and adequate in comparison to the experimental data.

Influence of force tremor on mechanomyographic signals recorded with an accelerometer and a condenser microphone during measurement of agonist and antagonist muscles in voluntary submaximal isometric contractions

The purpose of this study was to investigate the influence of force tremor (FT) on the mechanomyogram (MMG) recorded by a condenser microphone (MIC) and an accelerometer (ACC) for the measurement of agonist and antagonist muscles during submaximal isometric contractions. Following determination of the isometric maximum voluntary contraction (MVC), 10 male subjects were asked to perform elbow flexion and extension at 20%, 40%, 60%, and 80% MVC. Surface electromyogram (EMG) and MMG of the biceps brachii (BB) and triceps brachii (TB) were recorded simultaneously using a MIC (MMG-(MIC)) and an ACC (MMG-(ACC)). We analyzed the root mean square (RMS) for all signals and compared the sum of the power spectrum amplitude (SPA) at 3-6 Hz and 8-12 Hz between the MMG-(MIC) and the MMG-(ACC). During elbow flexion and extension, the RMS of the EMG and the MMG-(MIC) of the agonist were significantly (p<0.05) higher than those of the antagonist in each contraction level. The RMS of the MMG-(ACC) of the antagonist showed no significant (p>0.05) difference from that of the agonist, or tended to be higher than the agonist. The SPA of the MMG-(MIC) of the agonist at 3-6 Hz and 8-12 Hz tended to be higher than the antagonist in elbow flexion and extension at each contraction level. The SPA of the MMG-(ACC) of the agonist and that of the antagonist showed no significant (p>0.05) difference, or the antagonist MMG-(ACC) tended to be higher than that of the agonist. These results suggest the MMG detected by a MIC appears to be less affected by FT than is the ACC because of its inherent characteristic to reduce FT in simultaneously evaluated agonist and antagonist muscles by means of MMG during submaximal isometric contraction.