Cross recurrence quantification analysis of precision grip following peripheral median nerve block

Electrical-mechanical dynamical coupling between electrocardiographic and photoplethysmographic signals during cardiopulmonary resuscitation

BACKGROUND AND OBJECTIVE

Cardiac arrest (CA) remains a significant cause of death and disability. High-quality cardiopulmonary resuscitation (CPR) can improve the survival rate of CA. A challenging issue is to find physiological indicators for screening and evaluating the cardiovascular function associated with CPR. This study aimed to investigate the electrical-mechanical dynamic coupling between electrocardiographic (ECG) and photoplethysmographic (PPG) signals for indicating cardiovascular function in the progress of CPR.

METHOD

The ECG and PPG signals were simultaneously collected from a porcine CA model (n = 10) induced by ventricular fibrillation, and were further divided into four periods: Baseline, CA, CPR, and recovery of spontaneous circulation (ROSC). Recurrence quantitative analysis (RQA) was applied to examine the nonlinear dynamics of the ECG and PPG signals individually, and cross recurrence quantitative analysis (CRQA) was used to examine the ECG-PPG dynamical coupling.

RESULTS

The CA influenced the dynamic patterns of electrical and mechanical activities and the electrical-mechanical coupling, which can be observed from the reduced entropy (ENTR) (p < 0.01), reduced determinism (DET) (p < 0.01) and reduced trapping time (TT) (p < 0.01) at CA compared to Baseline. The recurrence rate (RR), ENTR, DET, and TT at CPR were significantly lower than the parameters at ROSC but higher than those at CA.

CONCLUSIONS

The electrical-mechanical dynamical coupling was sensitive to CPR and able to reflect the changes in cardiac function in the process of CPR.

Fine adaptive precision grip control without maximum pinch strength changes after upper limb neurodynamic mobilization

Before and immediately after passive upper limb neurodynamic mobilizations targeting the median nerve, grip (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF) and load (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF) forces applied by the thumb, index and major fingers (three-jaw chuck pinch) were collected using a manipulandum during three different grip precision tasks: grip-lift-hold-replace (GLHR), vertical oscillations (OSC), and vertical oscillations with up and down collisions (OSC/COLL/u, OSC/COLL/d). Several parameters were collected or computed from \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF. Maximum pinch strength and fingertips pressure sensation threshold were also examined. After the mobilizations, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF max changes from 3.2 ± 0.4 to 3.4 ± 0.4 N (p = 0.014), d\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF from 89.0 ± 66.6 to 102.2 ± 59.6 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N~\text{s}^{-1}$$\end{document}Ns-1 (p = 0.009), and d\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF from 43.6 ± 17.0 to 56.0 ± 17.9 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$N~\text{s}^{-1}$$\end{document}Ns-1 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<$$\end{document}p<0.001) during GLHR. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF SD changes from 0.9 ± 0.3 to 1.0 ± 0.2 N (p = 0.004) during OSC. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF peak changes from 17.4 ± 8.3 to 15.1 ± 7.5 N (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<$$\end{document}p<0.001), \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF from 12.4 ± 6.7 to 11.3 ± 6.8 N (p = 0.033), and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF from 2.9 ± 0.4 to 3.00 ± 0.4 N (p = 0.018) during OSC/COLL/u. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_F$$\end{document}GF peak changes from 13.5 ± 7.4 to 12.3 ± 7.7 N (p = 0.030) and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_F$$\end{document}LF from 14.5 ± 6.0 to 13.6 ± 5.5 N (p = 0.018) during OSC/COLL/d. Sensation thresholds at index and thumb were reduced (p = 0.001, p = 0.008). Precision grip adaptations observed after the mobilizations could be partly explained by changes in cutaneous median-nerve pressure afferents from the thumb and index fingertips.

Coupled Gluteus Maximus and Gluteus Medius Recruitment Patterns Modulate Hip Adduction Variability During Single-Limb Step-Downs: A Cross-Sectional Study

CONTEXT

Examining the coordinated coupling of muscle recruitment patterns may provide insight into movement variability in sport-related tasks.

OBJECTIVE

The purpose of this study was to examine the relationship between coupled gluteus maximus and medius recruitment patterns and hip-adduction variability during single-limb step-downs.

DESIGN

Cross-sectional.

SETTING

Biomechanics laboratory.

PARTICIPANTS

Forty healthy adults, including 26 women and 14 men, mean age 23.8 (1.6) years, mean body mass index 24.2 (3.1) kg/m2, participated.

INTERVENTIONS

Lower-extremity kinematics were acquired during 20 single-limb step-downs from a 19-cm step height. Electromyography (EMG) signals were captured with surface electrodes. Isometric hip-extension strength was obtained.

MAIN OUTCOME MEASURES

Hip-adduction variability, measured as the SD of peak hip adduction across 20 repetitions of the step-down task, was measured. The mean amplitudes of gluteus maximus and gluteus medius EMG recruitment were examined. Determinism and entropy of the coupled EMG signals were computed with cross-recurrence quantification analyses.

RESULTS

Hip-adduction variability correlated inversely with determinism (r = -.453, P = .018) and positively with entropy (r = .409, P = .034) in coupled gluteus maximus/medius recruitment patterns but not with hip-extensor strength nor with magnitudes of mean gluteus maximus or medius recruitment (r = -.003, .081, and .035; P = .990, .688, and .864, respectively).

CONCLUSION

Hip-adduction variability during single-limb step-downs correlated more strongly with measures of coupled gluteus maximus and medius recruitment patterns than with hip-extensor strength or magnitudes of muscle recruitment. Examining coupled recruitment patterns may provide an alternative understanding of the extent to which hip neuromuscular control modulates lower-extremity kinematics beyond examining muscle strength or EMG recruitment magnitudes.

Force-stabilizing synergies can be retained by coordinating sensory-blocked and sensory-intact digits

The present study examined the effects of selective digital deafferentation on the multi-finger synergies as a function of total force requirement and the number of digits involved in isometric pressing. 12 healthy adults participated in maximal and sub-maximal isometric pressing tasks with or without digital anesthesia to selective digits from the right hand. Our results indicate that selective anesthesia paradigm induces changes in both anesthetized (local) and non-anesthetized (non-local) digits’ performance, including: (1) decreased maximal force abilities in both local and non-local digits; (2) reduced force share during multi-finger tasks from non-local but not local digits; (3) decreased force error-making; and (4) marginally increased motor synergies. These results reinforce the contribution of somatosensory feedback in the process of maximal voluntary contraction force, motor performance, and indicate that somatosensation may play a role in optimizing secondary goals during isometric force production rather than ensuring task performance.

Cross-Recurrence Quantification Analysis for Inter-Muscular Coordination during Power Grip at Different Force Levels

This study aimed to examine the dynamical coordination across muscles during power grip at different force levels. Twenty-four healthy volunteers (12 males, 12 females) participated in this experiment. Subjects were instructed to grip a hydraulic hand dynamometer and produce forces at 30%, 50%, 70% Maximal Voluntary Contractions (MVC) for at least 10s, respectively. Surface electromyography (sEMG) signals were simultaneously recorded from eight muscles, including brachioradialis (BR), flexor carpi ulnaris (FCU), flexor carpi radialis (FCR), extensor digitorum communis (EDC), flexor digitorum superficialis (FDS), abductor pollicis brevis (APB), first dorsal interosseous (FDI) and abductor digiti minimi (ADM). A cross-recurrence quantification analysis (CRQA) was applied to analyze the sEMG signals by both visualization and quantifications. Results showed that percentage of determinism (%DET) and percentage of entropy (%ENT) of the extrinsic muscle pairs were augmented with increased force levels and had a weak but positive correlation. For intrinsic muscle pairs, the %DET and %ENT increased with force levels but the difference is not or less statistically significant. These results showed that the intermuscular coordination would be alter with force output increased. For the right-handers, the values of intrinsic muscles couplings in right hand were lower than left hand, because less coupled intrinsic muscles contribute to finger dexterity; the reason why the values of extrinsic muscles couplings in right hand were greater than left hand was stronger couplings of extrinsic muscles produced higher synergistic force.

Dynamical Coordination of Hand Intrinsic Muscles for Precision Grip in Diabetes Mellitus

This study investigated the effects of diabetes mellitus (DM) on dynamical coordination of hand intrinsic muscles during precision grip. Precision grip was tested using a custom designed apparatus with stable and unstable loads, during which the surface electromyographic (sEMG) signals of the abductor pollicis brevis (APB) and first dorsal interosseous (FDI) were recorded simultaneously. Recurrence quantification analysis (RQA) was applied to quantify the dynamical structure of sEMG signals of the APB and FDI; and cross recurrence quantification analysis (CRQA) was used to assess the intermuscular coupling between the two intrinsic muscles. This study revealed that the DM altered the dynamical structure of muscle activation for the FDI and the dynamical intermuscular coordination between the APB and FDI during precision grip. A reinforced feedforward mechanism that compensates the loss of sensory feedbacks in DM may be responsible for the stronger intermuscular coupling between the APB and FDI muscles. Sensory deficits in DM remarkably decreased the capacity of online motor adjustment based on sensory feedback, rendering a lower adaptability to the uncertainty of environment. This study shed light on inherent dynamical properties underlying the intrinsic muscle activation and intermuscular coordination for precision grip and the effects of DM on hand sensorimotor function.

Carpal tunnel syndrome impairs index finger responses to unpredictable perturbations

The fine-tuning of digit forces to object properties can be disrupted by carpal tunnel syndrome (CTS). CTS' effects on hand function have mainly been investigated using predictable manipulation tasks; however, unpredictable perturbations are commonly encountered during manual tasks, presenting situations which may be more challenging to CTS patients given their hand impairments. The purpose of this study was to investigate muscle and force responses of the index finger to unpredictable perturbations in patients with CTS. Nine CTS patients and nine asymptomatic controls were instructed to stop the movement of a sliding plate by increasing index finger force following an unexpected perturbation. The electrical activity of the first dorsal interosseous muscle and forces exerted by the index finger were recorded. CTS patients demonstrated 20.9% greater muscle response latency and 12.0% greater force response latency compared to controls (p<0.05). The duration of plate sliding was significantly different between groups (p<0.05); the CTS group's duration was 142.2±5.8ms compared to the control group's duration of 133.1±8.4ms. Although CTS patients had increased muscle and force response durations comparatively, these differences were not statistically significant. Findings from this study suggest CTS-induced sensorimotor deficits interfere with accurate detection, processing and response to unpredictable perturbations. These deficits could be accounted for at multiple levels of the peripheral and central nervous systems. Delayed and decreased responses may indicate inefficient object manipulation by CTS patients and may help to explain why CTS patients tend to drop objects.

Temporary Nerve Block at Selected Digits Revealed Hand Motor Deficits in Grasping Tasks

Peripheral sensory feedback plays a crucial role in ensuring correct motor execution throughout hand grasp control. Previous studies utilized local anesthesia to deprive somatosensory feedback in the digits or hand, observations included sensorimotor deficits at both corticospinal and peripheral levels. However, the questions of how the disturbed and intact sensory input integrate and interact with each other to assist the motor program execution, and whether the motor coordination based on motor output variability between affected and non-affected elements (e.g., digits) becomes interfered by the local sensory deficiency, have not been answered. The current study aims to investigate the effect of peripheral deafferentation through digital nerve blocks at selective digits on motor performance and motor coordination in grasp control. Our results suggested that the absence of somatosensory information induced motor deficits in hand grasp control, as evidenced by reduced maximal force production ability in both local and non-local digits, impairment of force and moment control during object lift and hold, and attenuated motor synergies in stabilizing task performance variables, namely the tangential force and moment of force. These findings implied that individual sensory input is shared across all the digits and the disturbed signal from local sensory channel(s) has a more comprehensive impact on the process of the motor output execution in the sensorimotor integration process. Additionally, a feedback control mechanism with a sensation-based component resides in the formation process for the motor covariation structure.

Effects of Tactile Sensitivity on Structural Variability of Digit Forces during Stable Precision Grip

This study investigated the effects of fingertip tactile sensitivity on the structural variability of thumb and index finger forces during stable precision grip. Thirty right-handed healthy subjects participated in the experiment. Transient perturbation of tactile afferents was achieved by wrapping up the distal pads of the thumb or index finger with transparent polyethylene films. The time-dependent structure of each digit force and the variability of interdigit force correlation were examined by detrended fluctuation analysis (DFA) and detrended cross-correlation analysis (DCCA), respectively. Results showed that the tactile sensitivity affected α_DFA of the vertical shear force Fx (F_3,239 = 6.814, p < 0.001) and α_DCCA of Fx (χ² = 16.440, p < 0.001). No significant difference was observed in α_DFA or α_DCCA of the normal forces produced by the thumb or index finger. These results suggested that with blurred tactile sensory inputs the central nervous system might decrease the vertical shear force flexibility and increase the interdigit shear force coupling in order to guarantee a stable grip control of an object against gravity. This study shed light on the feedback and feed-forward strategies involved in digit force control and the role of SA-II afferent fibers in regulation of vertical shear force variability for precision grip.

Coordination of digit force variability during dominant and non-dominant sustained precision pinch

This study examined the effects of handedness on the inter-digit coordination of force variability with and without concurrent visual feedback during sustained precision pinch. Twenty-four right-handed subjects were instructed to pinch an instrumented apparatus with their dominant and non-dominant hands, separately. During the pinch, the subjects were required to maintain a stable force output at 5 N for 1 min. Visual feedback was given for the first 30 s and removed for the second 30 s. Coefficient of variation and detrended fluctuation analysis were employed to examine the amount and structural variability of the thumb and index finger forces. Similarly, correlation coefficient and detrended cross-correlation analysis were applied to quantify the inter-digit correlation of force amount and structural variability. Results showed that, compared to the non-dominant hand, the dominant hand had higher inter-digit difference in the amount of digit force variability. Without visual feedback, the dominant hand exhibited lower digit force structural variability but higher inter-digit force structural correlation than the non-dominant hand. These results implied that the dominant hand would be more independent, less flexible and with lower dynamic degrees of freedom than the non-dominant hand in coordination of the thumb and index finger forces during sustained precision pinch. The effects of handedness on inter-digit force coordination were dependent on sensory condition, which shed light on higher-level sensorimotor mechanisms that may be responsible for the asymmetries in coordination of digit force variability.

Carpal tunnel syndrome impairs sustained precision pinch performance

OBJECTIVE

The purpose of this study was to investigate effects of carpal tunnel syndrome (CTS) on digit force control during a sustained precision pinch.

METHODS

Eleven CTS individuals and 11 age- and gender-matched healthy volunteers participated in the study. The subjects were instructed to isometrically pinch an instrumented apparatus for 60s with a stable force output. Visual feedback of force output was provided for the first 30s but removed for the remaining 30s. Pinch forces were examined for accuracy, variability, and inter-digit correlation.

RESULTS

CTS led to a decrease in force accuracy and an increase in amount of force variability, particularly without visual feedback (p<0.001). However, CTS did not affect the structure of force variability or force correlation between digits (p>0.05). The force of the thumb was less accurate and more variable than that of the index finger for both the CTS and healthy groups (p<0.001).

CONCLUSIONS

Sensorimotor deficits associated with CTS lead to inaccurate and unstable digit forces during sustained precision pinch.

SIGNIFICANCE

This study shed light on basic and pathophysiological mechanisms of fine motor control and aids in development of new strategies for diagnosis and evaluation of CTS.