Neuromuscular Control Modeling: from Physics to Data-Driven Approaches

Il controllo neurale della postura umana è stato investigato a partire da un punto di vista fisico. Il paradigma di controllo intermittente è stato usato allo scopo di capire il peso di quest'ultimo nella generazione delle traiettorie del centro di pressione. Un primo contributo di questo lavoro rigurda quindi l'analisi del centro di pressione generato dal suddetto modello biomeccanico attraverso l'extended detrended fluctuation analysis, recentemente proposta in letteratura. Le proprietà di correlazione a lungo termine e disomogeneità sono risultate strettamente legate al guadagno derivativo del modello di controllo intermittente e anche al grado di intermittenza. Il paradigma di controllo è stato poi esteso verso un sistema biomeccanico più complesso, cioè un pendolo inverso doppio link con controllo intermittente alla caviglia. I contributi più significativi hanno riguardato la modellazione matematica del centro di pressione per una struttura multi-link e la verifica della sua plausibilità fisiologica. Si è poi preso in considerazione il caso della postura perturbata, integrando aspetti cinematici, dinamici e relativi all'attività muscolare. A tal fine, si è utilizzato sia un approccio fisico che basato su dati per l'identificazione dei modelli a struttura variabile Si sono prese in considerazione differenti condizioni di sperimentali, e in tutti i casi l'approccio utilizzato ha garantito un adeguato grado di interpretabilità riguardo il ruolo del sistema nervoso centrale nella regolazione del postura eretta in condizioni perturbate. La seconda parte della tesi ha riguardato la caratterizzazione del controllo motorio attraverso il segnale elettromiografico di superfice. Il primo contributo ha riguardato l'identifcazione dell'onset muscolare in condizioni di basso rapporto segnale rumore, sfruttando operatori energetico di tipo Teager-Kaiser al fine del precondizionamento del segnale mioelettrico. La versioe estesa di questo tipo di operatori è risultata particolarmente utile al miglioramento delle performance di numerosi algoritmi di detection. Si è poi proseguito con l'utilizzo di tali segnali al fine della classificazione dei gesti dell'arto superiore. In particoalre si è prerso in considerazione il problema della motion intention detection dei principali movimenti della spalla , utilizzando sia descrittori del segnale elettromiografico nel dominio del tempo e della frequenza. Quest'ultimo aspetto risulta essere un elemento di novità nel contesto scientifico in quanto si sono considerati il riconoscimento l'intezioni di movimento di otto gesti della spalla con particolare attenzione al ruolo dei descrittori del segnale per la classificazione. Infine, con approcci simili, si è preso in considerazione il problema del riconoscimento della scrittura manuale a partire dal dato elettromiografico. Tale aspetto risulta poco investigato sotto la prospettiva della pattern recognition mioelettrica, ma la sua valenza è data dalla crescente richiesta di interfacce uomo-macchina per compiti riabilitativi che coinvolgono una componente cognitiva significativa, Inoltre, vista la tendenza ad investigare il ruolo del polso per il prelievo del segnale elettromiografico al fine della realizzazione delle suddette interfacce, si è analizzato l'utilizzo dei segnali elettromiografici del polso rispetto a quelli dell'avambraccio al fine di predirre le cifre scritte dall'utente, noto che l'avambraccio risulta essere la zona di prelievo più comunemente utilizzata.The biomechanics and the neural control of the human stance was investigated starting from a physical point of view. In particular the intermittent motor control paradigm was investigated with the aim of understanding how such paradigm mirrors in the center of pressure (COP) trajectories. A first contribution given in this work of thesis regards the analysis of COP generated from intermittent controlled inverted pendulum through the extended detrended fluctuation analysis, which was recently introduced in the literature. It has been found that the long-term correlation and inohmogeniety properties of the COP time series strictly depend on the derivative gain term of the intermittent controller and on the degree of intermittency of the control action. Thus, , another contribution provided in this work of thesis regards the use of a more complex biomechanical model of the stance, e.g. a double-link inverted pendulum intermittently controlled at the ankle. In terms of novelty, it deserves to be pointed out the results regarding the mechanical modeling of the COP for a multi-link structure, and the assessment of its physiological plausibility. . On the other hand, when the perturbed posture motor task was taken into account, there was the need to enlarge the perspective, integrating kinematic, dynamic and muscle activity data. The idea of employing different sources of information to develop models of the CNS represents an important element that was investigated using tools related to hybrid system identification theory. Subjects underwent to impulsive support base translations in three different conditions: considering eyes open, closed, and performing mental counting. Although such data were essentially analyzed through a data-driven approach, the identified models guaranteed physical interpretations of the role played by the CNS in the three different conditions. The second main core of this thesis regards the characterization of the motor control using the surface electromyographic (sEMG) signals. A first contribution given in this work regarded the muscle onset detection considering low SNR scenarios. In this framework, energy operators such as the Teager-Kaiser energy operator (TKEO) and its extended version (ETKEO) were investigated as signal preconditioning steps before the application of state of the art onset detection algorithms. The latter have been significantly boosted when ETKEO was used with respect to TKEO. The use of extended energy operators for the sEMG signal preprocessing constitutes a novel element in this field that can be also further investigated in future studies. From the sEMG muscle, one can also predict which movement the subject is going to perform. This aspect can be enclosed in the motion intention detection (MID) field. In this thesis a MID problem was investigated by taking into account two important aspects: as first the study was centered on the shoulder joint movements. Secondly, the MID problem was faced under a pattern recognition perspective. This allowed to verify whether methodologies encountered in the myoelectric hand gesture recognition can be transferred in the affine field of MID In contrast to what reported in the literature, where MID problems generally consider only few movements, in this work of thesis up to eight shoulder movements have been investigated. Myoelectric pattern recognition architectures were also used in the assessment of the ten hand-written digits. Despite the handwriting can be considered a hand movement that involves fine muscular control actions, it has not been consistently investigated in the field of sEMG based hand gesture recognition. Further, since the literature supports the change from forearm to wrist in order to acquire EMG data for hand gesture recognition, it was investigated whether such exchange can be performed when a challenging classification task, as the handwriting recognition has to be performed

On the Use of Fuzzy and Permutation Entropy in Hand Gesture Characterization from EMG Signals: Parameters Selection and Comparison

The surface electromyography signal (sEMG) is widely used for gesture characterization; its reliability is strongly connected to the features extracted from sEMG recordings. This study aimed to investigate the use of two complexity measures, i.e., fuzzy entropy (FEn) and permutation entropy (PEn) for hand gesture characterization. Fourteen upper limb movements, sorted into three sets, were collected on ten subjects and the performances of FEn and PEn for gesture descriptions were analyzed for different computational parameters. FEn and PEn were able to properly cluster the expected numbers of gestures, but computational parameters were crucial for ensuring clusters' separability and proper gesture characterization. FEn and PEn were also compared with other eighteen classical time and frequency domain features through the minimum redundancy maximum relevance algorithm and showed the best predictive importance scores in two gesture sets; they also had scores within the subset of the best five features in the remaining one. Further, the classification accuracies of four different feature sets presented remarkable increases when FEn and PEn are included as additional features. Outcomes support the use of FEn and PEn for hand gesture description when computational parameters are properly selected, and they could be useful in supporting the development of robotic arms and prostheses myoelectric control

EMG-Based Characterization of Walking Asymmetry in Children with Mild Hemiplegic Cerebral Palsy

5 May 2019; Accepted: 24 June 2019; Published: 27 June 2019 Abstract: Hemiplegia is a neurological disorder that is often detected in children with cerebral palsy. Although many studies have investigated muscular activity in hemiplegic legs, few EMG-based findings focused on una ected limb. This study aimed to quantify the asymmetric behavior of lower-limb-muscle recruitment during walking in mild-hemiplegic children from surface-EMG and foot-floor contact features. sEMG signals from tibialis anterior (TA) and gastrocnemius lateralis and foot-floor contact data during walking were analyzed in 16 hemiplegic children classified as W1 according to Winter’ scale, and in 100 control children. Statistical gait analysis, a methodology achieving a statistical characterization of gait by averaging surface-EMG-based features, was performed. Results, achieved in hundreds of strides for each child, indicated that in the hemiplegic side with respect to the non-hemiplegic side, W1 children showed a statistically significant: decreased number of strides with normal foot-floor contact; decreased stance-phase length and initial-contact sub-phase; curtailed, less frequent TA activity in terminal swing and a lack of TA activity at heel-strike. The acknowledged impairment of anti-phase eccentric control of dorsiflexors was confirmed in the hemiplegic side, but not in the contralateral side. However, a modified foot-floor contact pattern is evinced also in the contralateral side, probably to make up for balance requirements

In-shoe plantar shear stress sensor design, calibration and evaluation for the diabetic foot

Plantar shear stress may have an important role in the formation of a Diabetic Foot Ulcer, but its measurement is regarded as challenging and has limited research. This paper highlights the importance of anatomical specific shear sensor calibration and presents a feasibility study of a novel shear sensing system which has measured in-shoe shear stress from gait activity on both healthy and diabetic subjects. The sensing insole was based on a strain gauge array embedded in a silicone insole backed with a commercial normal pressure sensor. Sensor calibration factors were investigated using a custom mechanical test rig with indenter to exert both normal and shear forces. Indenter size and location were varied to investigate the importance of both loading area and position on measurement accuracy. The sensing insole, coupled with the calibration procedure, was tested one participant with diabetes and one healthy participant during two sessions of 15 minutes of treadmill walking. Calibration with different indenter areas (from 78.5 mm2 to 707 mm2) and different positions (up to 40 mm from sensor centre) showed variation in measurements of up to 80% and 90% respectively. Shear sensing results demonstrated high repeatability (>97%) and good accuracy (mean absolute error < ±18 kPa) in bench top mechanical tests and less than 21% variability within walking of 15-minutes duration. The results indicate the importance of mechanical coupling between embedded shear sensors and insole materials. It also highlights the importance of using an appropriate calibration method to ensure accurate shear stress measurement. The novel shear stress measurement system presented in this paper, demonstrates a viable method to measure accurate and repeatable in-shoe shear stress using the calibration procedure described. The validation and calibration methods outlined in this paper could be utilised as a standardised approach for the research community to develop and validate similar measurement technologies

On the Use of Fuzzy and Permutation Entropy in Hand Gesture Characterization from EMG Signals: Parameters Selection and Comparison

The surface electromyography signal (sEMG) is widely used for gesture characterization; its reliability is strongly connected to the features extracted from sEMG recordings. This study aimed to investigate the use of two complexity measures, i.e., fuzzy entropy (FEn) and permutation entropy (PEn) for hand gesture characterization. Fourteen upper limb movements, sorted into three sets, were collected on ten subjects and the performances of FEn and PEn for gesture descriptions were analyzed for different computational parameters. FEn and PEn were able to properly cluster the expected numbers of gestures, but computational parameters were crucial for ensuring clusters&rsquo; separability and proper gesture characterization. FEn and PEn were also compared with other eighteen classical time and frequency domain features through the minimum redundancy maximum relevance algorithm and showed the best predictive importance scores in two gesture sets; they also had scores within the subset of the best five features in the remaining one. Further, the classification accuracies of four different feature sets presented remarkable increases when FEn and PEn are included as additional features. Outcomes support the use of FEn and PEn for hand gesture description when computational parameters are properly selected, and they could be useful in supporting the development of robotic arms and prostheses myoelectric control

Robot Perception through Wearable Sensors: Decoding Grasping for Human-Robot Hand-Over

Human-robot interaction represents the cornerstone for the full development of Industry 4.0 and 5.0 paradigms, that rely on this cooperation in order to develop more efficient and flexible production lines. In this context, the human-robot handover plays a crucial role and many approaches were introduced to plan and control this task, including the less investigated decoding of human muscles activity. Hence, the design of reliable myoelectric human-robot interfaces is a point of primary interest. This paper investigates the use of a wearable device, i.e. an armband, for achieving a robust detection of several human grasping gestures. An evaluation of the most useful features, belonging to three different computational domains, is also proposed. Outcomes showed that high recognition performance can be achieved with limited computational burden, which is crucial when dealing with real-time demands in collaborative task

Single IMU Displacement and Orientation Estimation of Human Center of Mass: A Magnetometer-Free Approach

In this article, a self-contained procedure to estimate the vertical, medial–lateral, and anterior–posterior displacement of a single sacrum-worn inertial measurement unit (IMU) is presented, which can be related to the human body center of mass (CoM) displacement during treadmill walking through an adaptation of the sacral marker method. Furthermore, a magnetometer-free custom sensor-fusion algorithm for orientation estimation is proposed alongside a practical alignment procedure to refer relative IMU orientation estimation to a ground-fixed reference frame. Twelve healthy subjects performed two trials of treadmill walking at 3, 4, and 5 km/h for 150 s, with a sacrum-worn IMU. Orientation and displacement estimations were then compared with those obtained from an optoelectronic measurement system. Roll, pitch, and yaw angles showed root mean square error (RMSE) lower than 2° for walking trials at 3, 4, and 5 km/h, with Pearson’s correlation coefficient higher than 0.90 for each angle. Displacement accuracy was evaluated in terms of peak-to-trough distances and RMSE. Mean errors resulted lower than 1 mm for each axis of interest and for each gait speed, with RMSE not higher than 2.5 mm. The proposed off-line algorithm can be used in low-budget and infrastructure-free environments, to achieve reliable CoM displacement estimation during cyclic activities such as treadmill walking

A Minimal and Multi-Source Recording Setup for Ankle Joint Kinematics Estimation During Walking Using Only Proximal Information From Lower Limb

In this study, a minimal setup for the ankle joint kinematics estimation is proposed relying only on proximal information of the lower-limb, i.e. thigh muscles activity and joint kinematics. To this purpose, myoelectric activity of Rectus Femoris (RF), Biceps Femoris (BF), and Vastus Medialis (VM) were recorded by surface electromyography (sEMG) from six healthy subjects during unconstrained walking task. For each subject, the angular kinematics of hip and ankle joints were synchronously recorded with sEMG signal for a total of 288 gait cycles. Two feature sets were extracted from sEMG signals, i.e. time domain (TD) and wavelet (WT) and compared to have a compromise between the reliability and computational capacity, they were used for feeding three regression models, i.e. Artificial Neural Networks, Random Forest, and Least Squares - Support Vector Machine (LS-SVM). BF together with LS-SVM provided the best ankle angle estimation in both TD and WT domains (RMSE &#x003C; 5.6 deg). The inclusion of Hip joint trajectory significantly enhanced the regression performances of the model (RMSE &#x003C; 4.5 deg). Results showed the feasibility of estimating the ankle trajectory using only proximal and limited information from the lower limb which would maximize a potential transfemoral amputee user&#x2019;s comfortability while facing the challenge of having a small amount of information thus requiring robust data-driven models. These findings represent a significant step towards the development of a minimal setup useful for the control design of ankle active prosthetics and rehabilitative solutions

TWA Simulator: a Graphical User Interface for T-wave Alternans

T-wave alternans (TWA) is an every-other-beat fluctuation of the T-wave amplitude, often at microvolt (invisible) levels. It is recognized as an important risk index of severe ventricular arrhythmias, leading sometimes to sudden cardiac arrest. Many algorithms for automatic detection and quantification of TWA have been proposed; when applied to the same electrocardiogram (ECG), they may provide a different TWA quantification, making interpretation of differences difficult. Aim of this work is to propose TWA Simulator as a useful tool to validate and compare TWA identification methods. TWA Simulator is a user-friendly MATLAB graphical user interface (GUI) able to generate, model, visualize and store simulated ECG (SECG) affected by TWA of known morphology and amplitude. SECG is constructed by a Nfold repetition of a template, constituted by a real and clean ECG beat. Both number of beats and RR inter-beat variability can be set by the user. Both direct and inverted TWA can be simulated. Direct TWA is simulated by adding a waveform (among four possibility) to every other T wave; inverted TWA is simulated by changing T-wave polarity in every-other SECG beat. Availability of TWA Simulator would allow efficient validation and comparison of automatic TWA identification methods by helping interpretation of result

Role of the visual feedback on balance responses to upright stance perturbations

In this study an evaluation of visual feedback on the balance response to upright stance perturbations is proposed. Subjects underwent to base of support translations in backward direction at fixed velocity in an eye-open (EO) and eye-closed (EC) condition. Center of pressure (COP) and center of mass (COM) were acquired, showing a repeatable double-peak shape which mirrors two different response periods: a destabilizing phase and a counterbalancing phase. Thus, COP and COM were analyzed on the basis of their temporal and spatial features. Further, also the angular displacement of lower limb joints, trunk and head were considered and lower limb muscular activity in terms of myoelectric latencies. Results showed several differences in COP and COM based parameters between EO and EC condition. Moreover, angular range variations seemed to indicate a different role of each joint in the two considered sensory conditions, highlighting the switch from an ankle-based strategy (EO condition) to a more complex kinematic strategy (EC condition). Outcomes of this study could add information about: (A) the suitability of considering COP displacement in perturbed posture analyses with sensory deprivation and (B) the significant role of the visual feedback in balance maintenance when a sudden and quasi-impulsive disruption is employed