73 research outputs found
A Spark Of Emotion: The Impact of Electrical Facial Muscle Activation on Emotional State and Affective Processing
Facial feedback, which involves the brain receiving information about the activation of facial muscles, has the potential to influence our emotional states and judgments. The extent to which this applies is still a matter of debate, particularly considering a failed replication of a seminal study. One factor contributing to the lack of replication in facial feedback effects may be the imprecise manipulation of facial muscle activity in terms of both degree and timing. To overcome these limitations, this thesis proposes a non-invasive method for inducing precise facial muscle contractions, called facial neuromuscular electrical stimulation (fNMES). I begin by presenting a systematic literature review that lays the groundwork for standardising the use of fNMES in psychological research, by evaluating its application in existing studies. This review highlights two issues, the lack of use of fNMES in psychology research and the lack of parameter reporting. I provide practical recommendations for researchers interested in implementing fNMES. Subsequently, I conducted an online experiment to investigate participants' willingness to participate in fNMES research. This experiment revealed that concerns over potential burns and involuntary muscle movements are significant deterrents to participation. Understanding these anxieties is critical for participant management and expectation setting. Subsequently, two laboratory studies are presented that investigated the facial FFH using fNMES. The first study showed that feelings of happiness and sadness, and changes in peripheral physiology, can be induced by stimulating corresponding facial muscles with 5âseconds of fNMES. The second experiment showed that fNMES-induced smiling alters the perception of ambiguous facial emotions, creating a bias towards happiness, and alters neural correlates of face processing, as measured with event-related potentials (ERPs). In summary, the thesis presents promising results for testing the facial feedback hypothesis with fNMES and provides practical guidelines and recommendations for researchers interested in using fNMES for psychological research
Novel Bidirectional Body - Machine Interface to Control Upper Limb Prosthesis
Objective. The journey of a bionic prosthetic user is characterized by the opportunities and limitations involved in adopting a device (the prosthesis) that should enable activities of daily living (ADL). Within this context, experiencing a bionic hand as a functional (and, possibly, embodied) limb constitutes the premise for mitigating the risk of its abandonment through the continuous use of the device. To achieve such a result, different aspects must be considered for making the artificial limb an effective support for carrying out ADLs. Among them, intuitive and robust control is fundamental to improving amputeesâ quality of life using upper limb prostheses. Still, as artificial proprioception is essential to perceive the prosthesis movement without constant visual attention, a good control framework may not be enough to restore practical functionality to the limb. To overcome this, bidirectional communication between the user and the prosthesis has been recently introduced and is a requirement of utmost importance in developing prosthetic hands. Indeed, closing the control loop between the user and a prosthesis by providing artificial sensory feedback is a fundamental step towards the complete restoration of the lost sensory-motor functions. Within my PhD work, I proposed the development of a more controllable and sensitive human-like hand prosthesis, i.e., the Hannes prosthetic hand, to improve its usability and effectiveness.
Approach. To achieve the objectives of this thesis work, I developed a modular and scalable software and firmware architecture to control the Hannes prosthetic multi-Degree of Freedom (DoF) system and to fit all usersâ needs (hand aperture, wrist rotation, and wrist flexion in different combinations). On top of this, I developed several Pattern Recognition (PR) algorithms to translate electromyographic (EMG) activity into complex movements. However, stability and repeatability were still unmet requirements in multi-DoF upper limb systems; hence, I started by investigating different strategies to produce a more robust control. To do this, EMG signals were collected from trans-radial amputees using an array of up to six sensors placed over the skin. Secondly, I developed a vibrotactile system to implement haptic feedback to restore proprioception and create a bidirectional connection between the user and the prosthesis. Similarly, I implemented an object stiffness detection to restore tactile sensation able to connect the user with the external word. This closed-loop control between EMG and vibration feedback is essential to implementing a Bidirectional Body - Machine Interface to impact amputeesâ daily life strongly. For each of these three activities: (i) implementation of robust pattern recognition control algorithms, (ii) restoration of proprioception, and (iii) restoration of the feeling of the grasped object's stiffness, I performed a study where data from healthy subjects and amputees was collected, in order to demonstrate the efficacy and usability of my implementations. In each study, I evaluated both the algorithms and the subjectsâ ability to use the prosthesis by means of the F1Score parameter (offline) and the Target Achievement Control test-TAC (online). With this test, I analyzed the error rate, path efficiency, and time efficiency in completing different tasks.
Main results. Among the several tested methods for Pattern Recognition, the Non-Linear Logistic Regression (NLR) resulted to be the best algorithm in terms of F1Score (99%, robustness), whereas the minimum number of electrodes needed for its functioning was determined to be 4 in the conducted offline analyses. Further, I demonstrated that its low computational burden allowed its implementation and integration on a microcontroller running at a sampling frequency of 300Hz (efficiency). Finally, the online implementation allowed the subject to simultaneously control the Hannes prosthesis DoFs, in a bioinspired and human-like way. In addition, I performed further tests with the same NLR-based control by endowing it with closed-loop proprioceptive feedback. In this scenario, the results achieved during the TAC test obtained an error rate of 15% and a path efficiency of 60% in experiments where no sources of information were available (no visual and no audio feedback). Such results demonstrated an improvement in the controllability of the system with an impact on user experience.
Significance. The obtained results confirmed the hypothesis of improving robustness and efficiency of a prosthetic control thanks to of the implemented closed-loop approach. The bidirectional communication between the user and the prosthesis is capable to restore the loss of sensory functionality, with promising implications on direct translation in the clinical practice
Long term adaptations and mechanisms of different protocols of ''concurernt'' training in recreationally trained male adults.
The combination of resistance and endurance solicitations within the same training program or session appears to be a compulsory path to achieving high performance in many sports. Those performances are highly dependent on multiple physical qualities that must be developed simultaneously, whereas having appropriate concurrent training allows for better neuromuscular adaptation. Thus, the identification of a single form of physical training that promotes broad physical fitness adaptations within less time would be of great benefit to physical training specialists. Therefore, the general objective was to evaluate and compare the neuromuscular, metabolic, cardiorespiratory, structural (body composition and muscle architecture), and mechanical long-term adaptations between the three different concurrent training methods; Traditional Concurrent Training (TCT), Sprint Interval Training (SIT), and High-intensity Resistance Circuit-based training (HRC) in young recreationally training athletes. In addition, the specific objectives were to identify the long-term neuromuscular, metabolic, cardiorespiratory, structural (body composition and muscle architecture), and mechanical adaptation and mechanism following three different concurrent training (HRC, SIT, and TCT) in the same sample.
To achieve these objectives, the convenience sampling method was used for a single-blinded randomized controlled trial experimental research design to recruit thirty-four young recreationally training male athletes (24±5.8 years, 174.9±5.9 cm height, and 73.4±7.9 kg) and randomly assigned to three training groups (HRC: 13, SIT: 10, and TCT: 11). The study consisted of five total visits to the laboratory: Visit #1 â Initial assessment for requirement test and familiarization session, Visit #2 â pre-training evaluation, Visit #3 â continuation of pre-training evaluation, Visit #4 â post-training testing, and Visit #5 â continuation of post-training testing. The entire study has taken approximately ten weeks but all subjects exercised twice a week for 8 weeks during the intervention. During Visits # 2, 3, 4, and #5 neuromuscular, metabolic, cardiorespiratory, structural (body composition and muscle architecture), and mechanical variables were assessed. Standard descriptive statistics were used to characterize the study population. A mixed analysis of variance with repeated measures and the Bonferroni post hoc test were used to investigate the interaction effect and significant differences within and between groups.
The findings of the study are explained through five sections and the main findings of section 01 showed each training procedure had a unique neuronal adaptation that was most particular to its training character. Whereas SIT and TCT protocols demonstrated spinal adaptation throughout the intervention, HRC demonstrated supraspinal and spinal adaptation. It follows that while theoretically all of these adaptations exhibit both quantitatively positive and negative changes, both changes are crucial to improving athletic performance. Furthermore, the main findings of section 02 revealed that although no training approach is superior to the others, following three distinct concurrent training regimens caused different metabolic improvements in blood lipid profiles. Particularly, the TCT protocol was an ideal training method to lower total cholesterol levels and increase HDL-C, but SIT protocol is a time-effective method for performance-based programs that induced a decrease in cholesterol, triglycerides, and LDL-C, whereas HRC also induced positive and negative alterations. Thus, each user could be able to select any training protocol following their needs.
Moreover, section 03 exposed that the TCT protocol is much better than the other two concurrent training methods (HRC and SIT); in terms of enhancing the cardiorespiratory variables in recreationally trained individuals. However, following HRC and SIT also induced an increase in VO2 max and RMR, but the time consumed by the training sessions is lesser than TCT. Since HRC and SIT are very time efficient and contribute to enhancing cardiorespiratory adaptations, it would be advantageous to use a single mode of an exercise training protocol to improve cardiorespiratory variables. Hence, it is depending on the needs and desires of each individual in terms of their available time for exercising as well as the training plans.
In addition, section 04 observed that HRC, SIT, and TCT offered different body composition and muscle architecture benefits after the 8 weeks training period but no single program was better than another, but the time spent on the training sessions differed. Hence, depending on the necessity of the subjects they can select the training method for their training schedule. Need to write about the body composition
Interestingly, section 05 revealed that the HRC training program is better than other concurrent training protocols (SIT and TCT) for enhancing force and power in young recreational male athletes. Although HRC is recommended since it is so time-effective, the athlete's or coach's preferences may also call for the use of the other two training protocols throughout their training sessions.
Finally, it revealed that all training protocols enhance more or less adaptation respective to each other but some training methods are very time efficient than other training protocols. Thus, depending on the necessity of each athlete and their coaches they can select the training protocol for their training schedule.Actividad FĂsica y Deport
Smart Sensors for Healthcare and Medical Applications
This book focuses on new sensing technologies, measurement techniques, and their applications in medicine and healthcare. Specifically, the book briefly describes the potential of smart sensors in the aforementioned applications, collecting 24 articles selected and published in the Special Issue âSmart Sensors for Healthcare and Medical Applicationsâ. We proposed this topic, being aware of the pivotal role that smart sensors can play in the improvement of healthcare services in both acute and chronic conditions as well as in prevention for a healthy life and active aging. The articles selected in this book cover a variety of topics related to the design, validation, and application of smart sensors to healthcare
Modeling motor-evoked potentials from neural field simulations of transcranial magnetic stimulation
Objective
To develop a population-based biophysical model of motor-evoked potentials (MEPs) following transcranial magnetic stimulation (TMS).
Methods
We combined an existing MEP model with population-based cortical modeling. Layer 2/3 excitatory and inhibitory neural populations, modeled with neural-field theory, are stimulated with TMS and feed layer 5 corticospinal neurons, which also couple directly but weakly to the TMS pulse. The layer 5 output controls mean motoneuron responses, which generate a series of single motor-unit action potentials that are summed to estimate a MEP.
Results
A MEP waveform was generated comparable to those observed experimentally. The model captured TMS phenomena including a sigmoidal inputâoutput curve, common paired pulse effects (short interval intracortical inhibition, intracortical facilitation, long interval intracortical inhibition) including responses to pharmacological interventions, and a cortical silent period. Changes in MEP amplitude following theta burst paradigms were observed including variability in outcome direction.
Conclusions
The model reproduces effects seen in common TMS paradigms.
Significance
The model allows population-based modeling of changes in cortical dynamics due to TMS protocols to be assessed in terms of changes in MEPs, thus allowing a clear comparison between population-based modeling predictions and typical experimental outcome measures
Computational Intelligence in Electromyography Analysis
Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. EMG may be used clinically for the diagnosis of neuromuscular problems and for assessing biomechanical and motor control deficits and other functional disorders. Furthermore, it can be used as a control signal for interfacing with orthotic and/or prosthetic devices or other rehabilitation assists. This book presents an updated overview of signal processing applications and recent developments in EMG from a number of diverse aspects and various applications in clinical and experimental research. It will provide readers with a detailed introduction to EMG signal processing techniques and applications, while presenting several new results and explanation of existing algorithms. This book is organized into 18 chapters, covering the current theoretical and practical approaches of EMG research
Wavelet Theory
The wavelet is a powerful mathematical tool that plays an important role in science and technology. This book looks at some of the most creative and popular applications of wavelets including biomedical signal processing, image processing, communication signal processing, Internet of Things (IoT), acoustical signal processing, financial market data analysis, energy and power management, and COVID-19 pandemic measurements and calculations. The editorâs personal interest is the application of wavelet transform to identify time domain changes on signals and corresponding frequency components and in improving power amplifier behavior
Acupuncture in Modern Medicine
This book contains four integrated sections: 1) Acupuncture Research; 2) New Developments in Acupuncture; 3) Acupuncture Therapy for Clinical Conditions and 4) Assessment and Accessibility in Acupuncture Therapy. Section 1 provides updates on acupuncture research. From acupuncture effects in modulation of immune system to the role of nitric oxide in acupuncture mechanisms, chapters in this section offer readers the newest trends in acupuncture research. Section 2 summarizes new developments in acupuncture. The included chapters discuss new tools and methods in acupuncture such as laser acupuncture, sham needles, and new technologies. Section 3 discusses acupuncture therapy for clinical conditions. The chapters in this section provide comprehensive and critical views of acupuncture therapy and its application in common clinical practice. Section 4 takes a new look at the issues related to assessment and accessibility in acupuncture therapy. These issues are central to developing new standards for outcome assessment and policies that will increase the accessibility to acupuncture therapy
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