Vocal Cord Vibration Research Articles

Development of a Real-Time Wearable Humming Detector Device

This study focuses on the development of a wearable real-time Humming Detector Device (HDD) aimed at enhancing the control of assistive devices through humming. As the need for portable user-friendly tools in assistive technology grows, the HDD offers a non-invasive solution to detect vocal cord vibrations. Vibrations, detected thanks to an accelerometer worn on the neck, are processed in real time using a Fast Fourier Transform (FFT) to identify specific humming frequencies, which are then translated into commands for controlling assistive devices via Bluetooth Low Energy (BLE) transmission. The device was tested with 13 healthy subjects to validate its potential and determine the optimal number of distinct commands that users can achieve. The HDD’s portability and precision make it a promising alternative to traditional voice recognition systems, particularly for individuals with speech impairments.

Three-dimensional finite element analysis of biological signal feedback in the mechanical properties of sound production

In response to the problems of low reliability and long time consumption in traditional research on sound production, this article used electromyography (EMG) signals as input signals to build a high-precision sound production mechanics model. A Proportional-Integral-Derivative (PID) controller was used to dynamically adjust the model and develop a real-time feedback system. This article established a detailed three-dimensional (3D) finite element model including the vocal cords and throat, defined the nonlinear elastic properties and linear elastic properties of different tissues, and used tetrahedral grid partitioning technology to improve the computational accuracy of the model. Through a EMG sensor, an individual EMG was collected and filtered to remove noise. The processed EMGs were used as input parameters for the finite element model to drive the muscle units in the model. By using a PID controller to receive real-time EMG input, the error was calculated and the model was adjusted, enabling accurate simulation of the mechanical properties of vocal cord vibration under different vocal states and achieving real-time feedback. Considering the complexity of vocal cord vibration driven by biological signals, this article simulated and analyzed the modal characteristics of vocal cord vibration, and analyzed the differences in vocal cord vibration characteristics under different vocal states. The sound pressure distribution and resonance frequency were simulated and analyzed to understand the propagation characteristics of sound. Finally, by comparing and analyzing the simulated data with the actual collected data, it was found that the maximum relative error rate of the model under different sound states was 6.14%, and the overall error rate of the model was relatively low, which verified the reliability of the model. The findings demonstrated that the feedback delays of the model in different sound states were all within 100 milliseconds, indicating that the system had high real-time performance and accuracy, which was promising in practical applications.

Efficacy analysis of ansa cervicalis anterior root-recurrent laryngeal nerve anastomosis in the treatment of unilateral vocal cord paralysis

Objective:Investigates the application and clinical efficacy of ansa cervicalis anterior root-recurrent laryngeal nerve（RLN） anastomosis in the treatment of unilateral vocal fold paralysis（UVFP）. Methods:A prospective study was conducted with 92 UVFP patients admitted to our department from January 2018 to January 2022 who received ansa cervicalis anterior root-RLN anastomosis. The course of nerve injury ranged from 6 to 24 months. Videostroboscopy, voice subjective auditory perceptual assessment（GRBAS）, Voice Handicap Index（VHI-10）, voice objective acoustic analysis and laryngeal electromyography（EMG） were used to evaluate the efficacy of the operation. Results:Videostroboscopy showed that although the movement of vocal cords did not return to normal 12 months after operation, their volume and muscle tension were significantly improved and their positions were adducted to the median or near-median. Also the glottic closure, vocal cord position, vocal cord edge, symmetry and regularity of vocal cord vibration were significantly improved than pre-operation（P<0.01）. The five indexes of GRBAS（Grade, Roughness, Breathiness, Asthenia, Strain） and VHI-10, as well as voice acoustic parameters（Jitter, Shimmer, NHR） post-operation were significantly reduced, while the maximum phonation time（MPT） was significantly longer（P<0.01）. The results of laryngeal EMG indicated that the maximum voluntary motor unit recruitment（VMUR） post-operation was significantly recovered（P<0.01）, which confirmed that the affected laryngeal muscle obtained effective nerve reinnervation. Conclusion:Ansa cervicalis anterior root-RLN anastomosis can effectively improve the voice function of patients which is safe and satisfactory. It is an ideal method for the treatment of unilateral RLN injury.

Gallic acid melanin pigment hydrogel as a flexible macromolecule for articular motion sensing

In this study, water-soluble melanin was synthesized through the genetic recombination of Escherichia coli using gallic acid as a substrate. The recombinant host produced 2.83 g/L of gallic acid-based melanin (GA melanin) from 20 mM gallic acid. Notably, the isolated GA melanin demonstrated exceptional antioxidant and antimicrobial activities, exhibiting a 25.7 % inhibition ratio against Candida albicans. The structure and composition of GA melanin were analyzed using Fourier-transform infrared (FT-IR) spectroscopy, scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS), and X-ray diffraction (XRD). Remarkably, GA melanin displayed high thermal stability, maintaining integrity up to 1000 °C. Additionally, it exhibited unique electrical properties in terms of conductivity and resistivity compared to other common types of melanin. Subsequently, GA melanin was cross-linked with hydrogel to create a sensing template. The resulting GA melanin hydrogel demonstrated lower resistance (80.08 ± 3.0 kohm) compared to conventional hydrogels (108.62 ± 10.4 kohm), indicating an approximately 1.77-fold improvement in adhesion. Given its physical, biological, and electrical properties, the GA melanin hydrogel was further utilized as a flexible motion-sensing material to detect resistivity changes induced by knee, wrist, and finger bending, as well as vocal cord vibrations. In all cases, the sensing module displayed notable sensitivity to motion-induced resistivity variations.

Wearable self-powered motion sensor based on biomass carbon-dots/polyvinyl alcohol film

The functionalized polymer with scalable properties presents a promising option for flexible triboelectric nanogenerators designed for detecting human motion. In this study, a novel method to fabricate tribopositive composite film was proposed by incorporating high permittivity N-doped orange peel-based carbon dots (O-CDs) into the highly cross-linked polyvinyl alcohol (PVA). The O-CDs/PVA sensor showed elevated electrical output with the raised content of O-CDs until 1.5 wt. % with a peak voltage of 3.5 V. The response characteristics under various external force conditions were tested, and the maximum peak voltage and current reached 3.92 V and 28.6 A under the force of 50 N. Moreover, O-CDs/PVA sensors present superior high-output stability, durability, and accurate distinction to different movement states, even the vocal cord vibration. By introducing the support vector machine learning algorithm, intelligent gesture recognition was achieved. This work paves a facile, feasible, and scalable pathway to the self-powered human motion sensor device.

Highly sensitive flexible pressure sensor based on laser ablated Ag-MWCNT /MXene for human motion detection

The complex and dynamic human environment, higher requirements are put forward for the high-performance flexible pressure sensors. The materials selection and microstructure design are crucial to achieve high sensitivity and stability. In this work, we fabricated pressure sensitive layer with multiple dimensional materials. Using laser ablation in liquid method, Ag nanoparticles were uniformly distributed in surface of multi-walled carbon nanotubes (MWCNT). Combined with the delaminated MXene, highly pressure sensitive composite could be prepared due to the reduction of contact resistance under pressure. The corresponding piezoresistive sensors showed high sensitivity (12.7 kPa−1), excellent response speed (150 ms), recovery speed (100 ms), and distinguished cycle stability (3000 cycles). Based on the performance of the sensor, it can realize the monitoring of tiny pressure on the human body, and further realize the detection of human activities and health. In addition, the sensor array has spatial recognition capability, providing a way of thinking for the development needs of future intelligent wearable electronic devices. The sensors can measure changes in resistance caused by finger bending, slight breathing, pulse, vocal cord vibration, and other movements to realize human activity and health monitoring. At the same time, the 3×3 sensor array system can recognize the layout of pressure in space. This simple preparation and low cost of the sensor can Facilitate the progress towards sophisticated wearable electronic gadgets.

Ca2+/ethanol driven in-situ integration of tough, antifreezing and conductive silk fibroin/polyacrylamide hydrogels for wearable sensors and electronic skin

Integrating high strength, flexibility, biocompatibility, adhesion, and freezing resistance into conductive hydrogels for developing wearable electronic devices has consistently posed significant challenges in relevant research fields. Inspired by the silk dissolution behavior, a robust, flexible, antifreezing, and conductive silk fibroin/polyacrylamide (SF/PAM) hydrogel was synthesized in a CaCl2-ethanol–water (Ca2+/E/W) ternary solvent via a one-pot photogelation process. The gelation of SF and AM was enhanced by the ternary solvent, attributed to the inhibitory effects of Ca2+ ions and alcohols on hydrogen bond formation. The SF/PAM hydrogels based on Ca2+/E/W exhibited desirable mechanical properties (stretching: 800 % strain and 120 kPa stress; compression: 80 % strain and 334.0 kPa stress), excellent recoverability after deformation, high ion conductivity (2.4 S·cm−1) and strain sensitivity (gauge factor: ∼2.0), and low-temperature tolerance (−60 °C). These hydrogels were assembled into various wearable electronic devices, such as strain sensors, electronic skin, and electrodes, for detecting multiple physiological parameters, including joint activities, bioelectrical signals, and subtle movements like finger and wrist rotation, heartbeat, and vocal cord vibrations, demonstrating significant potential in flexible electronic applications.

Ultra-Stretchable Composite Organohydrogels Polymerized Based on MXene@Tannic Acid-Ag Autocatalytic System for Highly Sensitive Wearable Sensors.

Conductive hydrogels have attracted widespread attention in the fields of biomedicine and health monitoring. However, their practical application is severely hindered by the lengthy and energy-intensive polymerization process and weak mechanical properties. Here, a rapid polymerization method of polyacrylic acid/gelatin double-network organohydrogel is designed by integrating tannic acid (TA) and Ag nanoparticles on conductive MXene nanosheets as catalyst in a binary solvent of water and glycerol, requiring no external energy input. The synergistic effect of TA and Ag NPs maintains the dynamic redox activity of phenol and quinone within the system, enhancing the efficiency of ammonium persulfate to generate radicals, leading to polymerization within 10min. Also, ternary composite MXene@TA-Ag can act as conductive agents, enhanced fillers, adhesion promoters, and antibacterial agents of organohydrogels, granting them excellent multi-functionality. The organohydrogels exhibit excellent stretchability (1740%) and high tensile strength (184kPa). The strain sensors based on the organohydrogels exhibit ultrahigh sensitivity (GF=3.86), low detection limit (0.1%), and excellent stability (>1000 cycles, >7 days). These sensors can monitor the human limb movements, respiratory and vocal cord vibration, as well as various levels of arteries. Therefore, this organohydrogel holds potential for applications in fields such as human health monitoring and speech recognition.

Flexible and washable MXene@PEDOT:PSS@CS@PU pressure sensors

Flexible electronics have attracted great interest because of their potential applications in healthcare monitoring and human-computer interaction. The performance of flexible electronics depends on the design of structure, materials, and mechanical responses. In this work, we explore the use of polyurethane (PU) sponge as the scaffold to form flexible piezoresistive pressure sensors with conductive networks made from conductive polymer PEDOT:PSS and MXene nanosheets. The sensitivity of the prepared pressure sensors reaches 0.2171 kPa−1 under mechanical pressure in a range of 1.8–6.15 kPa. The prepared pressure sensors are re-usable after washing. The applications of the prepared pressure sensors in the sensing of physiological behavior are demonstrated under the action of finger tapping, finger bending, vocal cord vibration, swallowing, and pulsing of radial artery. The prepared pressure sensors have great prospects for applications in human-machine interaction and physiological diagnosis.

3D printed MXene/rGO hierarchical porous structure based on ultralow-concentration 2D nanomaterial inks for highly sensitive pressure sensing

3D direct ink writing technology based on two-dimensional (2D) MXene nanomaterial inks receives attention in the field of pressure sensing for simplicity of fabrication, programmable geometry with controllable function and performance. However, it is still a huge challenge to print excellent macro-structure with ultralow-concentration MXene inks, attributed to its weak gelation ability. Herein, we construct a MXene/reduced graphene oxide (MX/rGO) architecture (0.012 g cm−3) with macroscopic (hierarchical lattice) and microscopic (porous) structure by using ultralow-concentration emulsion-based inks of MXene (5.882 mg mL−1). The introduction of octadecylamine enhances the bonding between the MXene and GO, significantly improving the gelation ability of the ink with low-concentration 2D nanomaterials. More importantly, the MX/rGO pressure sensor achieves a high sensitivity (166.957 kPa−1), wide sensing range (0.028∼100 kPa), and excellent cyclic stability (10500 cycles) due to its 3D hierarchical lattice porous structure. These sensing capabilities enable the sensor to detect various human motions, such as pulse beating, vocal cord vibration, facial expressions, different joint movements and pressure distribution. Undoubtedly, this work provides a broad development prospect for the customized flexible pressure sensors based on MXene ink 3D printing technology.

A flexible PTI-CNT strain sensor with high stretchable and sensitive for human movement and vocal cord vibration monitoring

Flexible strain sensors possess significant application potential in wearable electronics, as they enable the monitoring of physical signals from extensive human movements and subtle motions. Despite the increasing demand for conductive and elastic materials in strain-sensing applications for wearable electronic devices, attaining exceptional and balanced mechanical performance while maintaining high conductivity remains challenging. In this work, we developed a novel polyurethane elastomer sensor material (referred to as PTI-CNTs) composed of polycaprolactone triol (PCT-L), isophorone diisocyanate (IPDI) and carbon nanotubes (CNTs). The elongation at break of the PTI-CNTs3% material can reach 866.70%, representing a 44.00% increase compared to pure PTI. The PTI-CNTs3% sensors exhibited high sensitivity (GF = 23.12) and excellent stability (with the cycle stretching time exceeding 5000 s). The flexible sensors displayed a satisfactory response time of 300 ms, enabling the detection of extensive human movements, including bending of the finger, wrist, elbow, knee, and ankle, as well as subtle motions like swallowing and phonation. Due to the easy and economical fabrication process, high sensitivity, and good reversibility of PTI-CNTs3% sensors, they have great potential for use in wearable health monitoring devices applications.

A High-Performance Strain Sensor for the Detection of Human Motion and Subtle Strain Based on Liquid Metal Microwire.

Flexible strain sensors have a wide range of applications, such as human motion monitoring, wearable electronic devices, and human-computer interactions, due to their good conformability and sensitive deformation detection. To overcome the internal stress problem of solid sensing materials during deformation and prepare small-sized flexible strain sensors, it is necessary to choose a more suitable sensing material and preparation technology. We report a simple and high-performance flexible strain sensor based on liquid metal nanoparticles (LMNPs) on a polyimide substrate. The LMNPs were assembled using the femtosecond laser direct writing technology to form liquid metal microwires. A wearable strain sensor from the liquid metal microwire was fabricated with an excellent gauge factor of up to 76.18, a good linearity in a wide sensing range, and a fast response/recovery time of 159 ms/120 ms. Due to these extraordinary strain sensing performances, the strain sensor can monitor facial expressions in real time and detect vocal cord vibrations for speech recognition.

Vocal Cord Vibration Signal Recognition Model Based on Feature Engineering Preprocessing

Vocal Cord Vibration Signal Recognition Model Based on Feature Engineering Preprocessing

Achieving ultrasensitivity and high breathability in biodegradable piezoresistive electronic skins

Nonbiodegradable components, such as synthetic polymers, have been widely used in the fabrication of flexible piezoresistive sensors and electronic skins (e-skins), resulting in the generation of electronic waste (e-waste) and toxic by-products. To overcome this issue, a wide range of biodegradable natural biopolymers and synthetic polymers have been employed. However, most of the current biodegradable e-skins demonstrate limitations such as low sensitivity, poor electrical conductivity, limited breathability, and low stability. To address these limitations, this study proposes a highly breathable and ultrasensitive piezoresistive e-skin based on the oxidized single-walled carbon nanotube (Ox-SWCNT)/silver nanowire (AgNW)-coated leaf skeletons. The developed disposable piezoresistive e-skin exhibits a remarkable performance including high sensitivity (19.75 ± 1.5 kPa−1, <3 kPa), sensing range of ≤42 kPa, ultralow limit of detection (∼0.27 Pa), linearity for low- and high-pressure regimes, high flexibility, high stability (3000 cycles), low weight, ultrahigh breathability, and biodegradability. In addition, the developed leaf-based e-skin demonstrates outstanding sensing performance in human-motion monitoring by detecting various motions such as subtle and vigorous flexions, airflow, and vocal-cord vibrations. The proposed piezoresistive e-skin is a promising platform for the development of various low-cost, biocompatible, fully biodegradable, and point-of-care (POC) e-skins for a wide range of subtle and vigorous pressure-monitoring applications including human–machine interfaces (HMIs), robotics, prosthesis, and flexible electronics.

Triple physical cross-linking cellulose nanofibers-based poly(ionic liquid) hydrogel as wearable multifunctional sensors

A novel triple physical cross-linking poly(ionic liquid) hydrogel, composed of poly(acrylamide-co-dodecyl methacrylate-co-1-vinyl-3-methyluracil-imidazolium chloride)/cellulose nanofibers-Ca2+ (PADV/CNFs-Ca2+), was synthesized through micellar-copolymerization followed by a solvent-soaked procedure. The synergistic interactions in polymer network (i.e. the hydrophobic association of dodecyl methacrylate moiety in surfactant micelles, the hydrogen bondings between imidazolium monomer segments and other monomer segments in polymers, and the ionic coordination between Ca2+ and -COO− on cellulose nanofibers surface) endowed the hydrogel with excellent mechanical properties, including high strength (754 kPa of tensile strength and 1905 kPa of compressive strength), outstanding stretchability (1963 %), elastic modulus (56.5 kPa) and remarkable mechanical durability (200 cycles with 500 % deformations and 100 cycles at 50 % compression strain). Besides, this hydrogel exhibited other advantages, such as satisfied conductivity (28.7 mS/cm), high strain/pressure/temperature-sensitive behavior, precise and stable signal transmission, varying degrees of antibacterial activity, and biocompatibility. Owing to the exceptional comprehensive performance, the hydrogel was then assembled as a multifunctional sensor to monitor the joint motion, vocal cord vibration, tactile sensation and body temperature with remarkable sensitivity in real time. This work offered a new strategy for the fabrication of durable, biocompatible, antibacterial and conductive materials for wearable multifunctional electronic devices.

Fully flexible and mechanically robust tactile sensors containing core–shell structured fibrous piezoelectric mat as sensitive layer

Tactile sensors based on poly(vinylidene fluoride) (PVDF) are widely investigated, but their flexibility and mechanical robustness are limited due to the poor elasticity of PVDF. Herein, fully flexible and mechanically robust tactile sensors with a sandwich-like structure are fabricated by introducing a core–shell structured fibrous piezoelectric mat between two fibrous TPU/AgNWs (TPU: thermoplastic polyurethane, AgNWs: silver nanowires) flexible electrodes. The piezoelectric mat works as the sensitive layer, in which TPU is designed as the elastic skeleton in the core of fibers to enhance the mechanical properties while PVDF is wrapped on TPU fiber as a piezoelectric component. The core–shell structured TPU/PVDF mat has achieved improved elasticity and stretchability and excellent piezoelectric effects are demonstrated (sensitivity: 95.8 mV N−1). Because of the flexibility of both sensitive layer and electrodes, the tactile sensors have achieved an elongation of 300 %, excellent elasticity, a sensitivity of 20.3 mV N−1 and stable sensing in more than 2,000 cycles. Interestingly, such tactile sensors also exhibit outstanding mechanical robustness and have the ability to properly respond to mechanical stimuli in deformed states. Various pressures generated in daily life (e.g., hand slapping, feather brushing, joint bending, blowing, vocal cord vibration and writing) are successfully monitored utilizing such tactile sensors. Overall, this work has provided a new clue to regulate the flexibility and mechanically robustness of tactile sensors.

Ultra-stretchable, antifreezing, and self-healing ZnO nanofluid-based hydrogels for triboelectric nanogenerators and self-powered biosensors

Flexible, self-healing, and highly sensitive wearable self-powered sensors are essential for promoting the rapid development of wearable electronics. Herein, a hydrogel based on zinc oxide nanofluids (AP-Zn) was synthesized using 2-acrylamido-2-methylpropane sulfonic acid and polyethylene glycol diacrylate. The AP-Zn hydrogel exhibits excellent stretchability (2750 %), high conductivity (1.37 S m−1), antifreezing capabilities (−20 °C), and self-healing abilities. Furthermore, the AP-Zn hydrogel was utilized to construct a triboelectric nanogenerator (AP-Zn-TENG), which demonstrated outstanding electrical output performance, with an open-circuit voltage, short-circuit current, and maximum power density of 135 V, 4.0 μA, and 1.39 W m−2, respectively. As a pressure sensor, the AP-Zn-TENG has a detection limit of 0.025 kPa and can even detect vocal cord vibrations of different pitches. Therefore, the AP-Zn-TENG self-powered sensor can be employed for detecting human behavior. These results suggest that the AP-Zn hydrogel holds great promise in wearable power technology and self-powered biosensors.

The Use of a Dehydrated Cellularized Collagen Matrix to Replace Fibrotic Vocal Fold Mucosa.

Fibrosis of the vocal fold lamina propria reduces vocal cord vibration resulting in a chronically hoarse voice. We describe a novel approach using umbilical cord-derived mesenchymal stem cells in a dehydrated collagen matrix (cellogen) to reconstruct the delicate balance of extracellular matrix within the vocal fold lamina propria whilst limiting the host inflammatory response to the implant. Human umbilical cord-derived mesenchymal stem-cells were embedded in bovine type I collagen hydrogel and dehydrated using the RAFT™ 3D culture system. The extracellular matrix, cellular viability and composition, paracrine profile, and genomic profile were assessed and the scaffold engrafted onto the hind muscle of NUDE mice. The cells retained stem-cell markers following fabrication and secreted collagen III, fibronectin, and glycosaminoglycans within the scaffold. Electron microscopy showed the scaffold consisted of single strands of protein with interspersed bundles of a similar size to native vocal fold lamina propria. The use of the dehydration step improved cell viability and upregulated the expression of genes important in wound healing and matrix organization compared with unmodified collagen hydrogel carriers. The cells were shown to secrete exosomes and cytokines and, following engraftment within an immunocompromised mouse model, appeared to modulate the host inflammatory response compared with controls. This article provides a scalable cell-protein scaffold that with further modifications could provide a replacement for lost or damaged vocal fold mucosa. Further investigations are required to assess the mechanical properties of the scaffold and inhibit the differentiation of the umbilical cord-derived stem-cells following implantation. Laryngoscope, 134:882-893, 2024.

Plasmon-enhanced photoacoustic oscillation for micro laser motor actuation

Flexible micro/nano motors responsive to light sources are highly desirable. Conventional photothermal (PT) techniques have provided significant light-actuation methods; however, the dynamic responses of these devices in high frequency domain are severely restricted by the frequency response limitation. To overcome this limitation, the thermal-, electric-, and acoustic-near field interactions in the PT process and its accompanied photoacoustic (PA) process are investigated, and a plasmon enhanced PA actuation method is proposed. The significant improvement in PA oscillation by strong localized surface plasmon resonance provides a powerful means to realize a broadband response laser motor without the frequency response limitation. This PA laser motor could generate PA oscillation of over 5 µm by pulse laser with repetition frequencies of 1 Hz to 20 kHz and has a maximum value of 18.8 µm at the mechanical resonant frequency. It demonstrates the effectiveness of this PA laser motor in offsetting the shortcomings of the PT actuation method. The device requires no electrical or chemical energy, and it has potential benefits, such as bionic research into insect flapping, vocal-cord vibration, and muscular movement in fields including micro/nano physics, biochemistry, and clinical medicine.

Analysis and Investigation of Speaker Identification Problems Using Deep Learning Networks and the YOHO English Speech Dataset

The rapid momentum of deep neural networks (DNNs) in recent years has yielded state-of-the-art performance in various machine-learning tasks using speaker identification systems. Speaker identification is based on the speech signals and the features that can be extracted from them. In this article, we proposed a speaker identification system using the developed DNNs models. The system is based on the acoustic and prosodic features of the speech signal, such as pitch frequency (vocal cords vibration rate), energy (loudness of speech), their derivations, and any additional acoustic and prosodic features. Additionally, the article investigates the existing recurrent neural networks (RNNs) models and adapts them to design a speaker identification system using the public YOHO LDC dataset. The average accuracy of the system was 91.93% in the best experiment for speaker identification. Furthermore, this paper helps uncover reasons for analyzing speakers and tokens yielding major errors to increase the system’s robustness regarding feature selection and system tune-up.