Prosodic Preferences of Surface Electromyography-based Subvocal Speech for People With Laryngectomy.

Introduction: People who undergo a total laryngectomy lose their natural voice and depend on alaryngeal technologies for communication. However, these technologies are often difficult to use and lack prosody. Surface electromyographic-based silent speech interfaces are novel communication systems that overcome many of the shortcomings of traditional alaryngeal speech and have the potential to seamlessly incorporate individualized prosody.

System Architecture for VR Yoga Therapy Platform with 6-DoF Whole-Body Avatar Tracking.

Chronic pain is a leading cause of morbidity among children and adolescents affecting 35% of the global population. Pediatric chronic pain management requires integrative health methods spanning physical and psychological subsystems through various mind-body interventions. Yoga therapy is one such method, known for its ability to improve the quality of life both physically and psychologically in chronic pain conditions.

A Virtual Reality Exergame: Clinician-Guided Breathing and Relaxation for Children with Muscular Dystrophy.

This study introduces a VR-based breathing and relaxation exergame tailored for individuals with Duchenne muscular dystrophy (DMD). DMD is a rare neuromuscular disease that leads to respiratory muscle dysfunction with anxiety being a common comorbidity. Clinical management requires frequent visits to rare disease specialists to manage symptom progression.

Ability-Based Methods for Personalized Keyboard Generation.

This study introduces an ability-based method for personalized keyboard generation, wherein an individual's own movement and human-computer interaction data are used to automatically compute a personalized virtual keyboard layout. Our approach integrates a multidirectional point-select task to characterize cursor control over time, distance, and direction. The characterization is automatically employed to develop a computationally efficient keyboard layout that prioritizes each user's movement abilities through capturing directional constraints and preferences.

Prediction of Voice Fundamental Frequency and Intensity from Surface Electromyographic Signals of the Face and Neck.

Silent speech interfaces (SSIs) enable speech recognition and synthesis in the absence of an acoustic signal. Yet, the archetypal SSI fails to convey the expressive attributes of prosody such as pitch and loudness, leading to lexical ambiguities. The aim of this study was to determine the efficacy of using surface electromyography (sEMG) as an approach for predicting continuous acoustic estimates of prosody.

Ability-based Keyboards for Augmentative and Alternative Communication: Understanding How Individuals' Movement Patterns Translate to More Efficient Keyboards: Methods to Generate Keyboards Tailored to User-specific Motor Abilities.

This study presents the evaluation of ability-based methods extended to keyboard generation for alternative communication in people with dexterity impairments due to motor disabilities. Our approach characterizes user-specific cursor control abilities from a multidirectional point-select task to configure letters on a virtual keyboard based on estimated time, distance, and direction of movement. These methods were evaluated in three individuals with motor disabilities against a generically optimized keyboard and the ubiquitous QWERTY keyboard.

Surface Electromyography-Based Recognition, Synthesis, and Perception of Prosodic Subvocal Speech.

Purpose This study aimed to evaluate a novel communication system designed to translate surface electromyographic (sEMG) signals from articulatory muscles into speech using a personalized, digital voice. The system was evaluated for word recognition, prosodic classification, and listener perception of synthesized speech. Method sEMG signals were recorded from the face and neck as speakers with ( = 4) and without ( = 4) laryngectomy subvocally recited (silently mouthed) a speech corpus comprising 750 phrases (150 phrases with variable phrase-level stress).

Motor unit drive: a neural interface for real-time upper limb prosthetic control.

Objective: Modern prosthetic limbs have made strident gains in recent years, incorporating terminal electromechanical devices that are capable of mimicking the human hand. However, access to these advanced control capabilities has been prevented by fundamental limitations of amplitude-based myoelectric neural interfaces, which have remained virtually unchanged for over four decades. Consequently, nearly 23% of adults and 32% of children with major traumatic or congenital upper-limb loss abandon regular use of their myoelectric prosthesis.

Development of sEMG sensors and algorithms for silent speech recognition.

Objective: Speech is among the most natural forms of human communication, thereby offering an attractive modality for human-machine interaction through automatic speech recognition (ASR). However, the limitations of ASR-including degradation in the presence of ambient noise, limited privacy and poor accessibility for those with significant speech disorders-have motivated the need for alternative non-acoustic modalities of subvocal or silent speech recognition (SSR).

Approach: We have developed a new system of face- and neck-worn sensors and signal processing algorithms that are capable of recognizing silently mouthed words and phrases entirely from the surface electromyographic (sEMG) signals recorded from muscles of the face and neck that are involved in the production of speech.

Silent Speech Recognition as an Alternative Communication Device for Persons with Laryngectomy.

Each year thousands of individuals require surgical removal of their larynx (voice box) due to trauma or disease, and thereby require an alternative voice source or assistive device to verbally communicate. Although natural voice is lost after laryngectomy, most muscles controlling speech articulation remain intact. Surface electromyographic (sEMG) activity of speech musculature can be recorded from the neck and face, and used for automatic speech recognition to provide speech-to-text or synthesized speech as an alternative means of communication.

Contribution from motor unit firing adaptations and muscle coactivation during fatigue.

The control of motor unit firing behavior during fatigue is still debated in the literature. Most studies agree that the central nervous system increases the excitation to the motoneuron pool to compensate for decreased force contributions of individual motor units and sustain muscle force output during fatigue. However, some studies claim that motor units may decrease their firing rates despite increased excitation, contradicting the direct relationship between firing rates and excitation that governs the voluntary control of motor units.

Lead (Pb) neurotoxicology and cognition.

Lead (Pb) is a neurotoxic substance. While it is widely understood that Pb exposure in early childhood adversely impacts neurodevelopment and intelligence, other aspects of cognition that are negatively affected, and the neuroanatomy and neurophysiology underlying Pb-related cognitive impairment are not widely appreciated by clinicians. This critical review gives a broad synopsis of the current literature in the field.

The compensatory interaction between motor unit firing behavior and muscle force during fatigue.

Throughout the literature, different observations of motor unit firing behavior during muscle fatigue have been reported and explained with varieties of conjectures. The disagreement amongst previous studies has resulted, in part, from the limited number of available motor units and from the misleading practice of grouping motor unit data across different subjects, contractions, and force levels. To establish a more clear understanding of motor unit control during fatigue, we investigated the firing behavior of motor units from the vastus lateralis muscle of individual subjects during a fatigue protocol of repeated voluntary constant force isometric contractions.

Synchronization of motor unit firings: an epiphenomenon of firing rate characteristics not common inputs.

Synchronous motor unit firing instances have been attributed to anatomical inputs shared by motoneurons. Yet, there is a lack of empirical evidence confirming the notion that common inputs elicit synchronization under voluntary conditions. We tested this notion by measuring synchronization between motor unit action potential trains (MUAPTs) as their firing rates progressed within a contraction from a relatively low force level to a higher one.

Decomposition of surface EMG signals from cyclic dynamic contractions.

Over the past 3 decades, various algorithms used to decompose the electromyographic (EMG) signal into its constituent motor unit action potentials (MUAPs) have been reported. All are limited to decomposing EMG signals from isometric contraction. In this report, we describe a successful approach to decomposing the surface EMG (sEMG) signal collected from cyclic (repeated concentric and eccentric) dynamic contractions during flexion/extension of the elbow and during gait.

Error reduction in EMG signal decomposition.

Decomposition of the electromyographic (EMG) signal into constituent action potentials and the identification of individual firing instances of each motor unit in the presence of ambient noise are inherently probabilistic processes, whether performed manually or with automated algorithms. Consequently, they are subject to errors. We set out to classify and reduce these errors by analyzing 1,061 motor-unit action-potential trains (MUAPTs), obtained by decomposing surface EMG (sEMG) signals recorded during human voluntary contractions.

Statistically rigorous calculations do not support common input and long-term synchronization of motor-unit firings.

Over the past four decades, various methods have been implemented to measure synchronization of motor-unit firings. In this work, we provide evidence that prior reports of the existence of universal common inputs to all motoneurons and the presence of long-term synchronization are misleading, because they did not use sufficiently rigorous statistical tests to detect synchronization. We developed a statistically based method (SigMax) for computing synchronization and tested it with data from 17,736 motor-unit pairs containing 1,035,225 firing instances from the first dorsal interosseous and vastus lateralis muscles--a data set one order of magnitude greater than that reported in previous studies.

Transposed firing activation of motor units.

Muscles are composed of groups of muscle fibers, called motor units, each innervated by a single motoneuron originating in the spinal cord. During constant or linearly varying voluntary force contractions, motor units are activated in a hierarchical order, with the earlier-recruited motor units having greater firing rates than the later-recruited ones. We found that this normal pattern of firing activation can be altered during oscillatory contractions where the force oscillates at frequencies ≥2 Hz.