Yaolong Lou

Continual Monitoring of Respiratory Disorders to Enhance Therapy via Real-Time Lung Sound Imaging in Telemedicine

Electronics, Apr 26, 2024

This work presents a configurable Internet of Things architecture for acoustical sensing and anal... more This work presents a configurable Internet of Things architecture for acoustical sensing and analysis for frequent remote respiratory assessments. The proposed system creates a foundation for enabling real-time therapy and patient feedback adjustment in a telemedicine setting. By allowing continuous remote respiratory monitoring, the system has the potential to give clinicians access to assessments from which they could make decisions about modifying therapy in real-time and communicate changes directly to patients. The system comprises a wearable wireless microphone array interfaced with a programmable microcontroller with embedded signal conditioning. Experiments on the phantom model were conducted to demonstrate the feasibility of reconstructing acoustic lung images for detecting obstructions in the airway and provided controlled validation of noise resilience and imaging capabilities. An optimized denoising technique and design innovations provided 7 dB more SNR and 7% more imaging accuracy for the proposed system, benchmarked against digital stethoscopes. While further clinical studies are warranted, initial results suggest potential benefits over single-point digital stethoscopes for internet-enabled remote lung monitoring needing noise immunity and regional specificity. The flexible architecture aims to bridge critical technical gaps in frequent and connected respiratory function at home or in busy clinical settings challenged by ambient noise interference.

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An Acoustic System of Sound Acquisition and Image Generation for Frequent and Reliable Lung Function Assessment

IEEE Sensors Journal, Dec 31, 2022

The Effect of Sensor Array Design on Acoustic Imaging for Enhancing HFCWO Therapy

Locating Nidi for High-Frequency Chest Wall Oscillation Smart Therapy via Acoustic Imaging of Lung Airways as a Spatial Network

IEEE Access

This work was supported by the Singapore Economic Development Board (EDB) and provides sponsorshi... more

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Design of a Robust Lung Sound Acquisition System for Reliable Acoustic Lung Imaging

2023 IEEE International Ultrasonics Symposium (IUS)

A Hybrid Approach of Wavelet-based Total Variation and Wiener Filter to Denoise Adventitious Lung Sound Signal for an Accurate Assessment

2022 IEEE International Conference on Consumer Electronics (ICCE), Jan 7, 2022

Adventitious sounds and their characteristics are the critical indicators of lung dysfunctions. U... more Adventitious sounds and their characteristics are the critical indicators of lung dysfunctions. Unfortunately, the captured lung sound often contains noise interferences, which may hinder the accuracy assessment of lung health. This paper proposes a hybrid approach of wavelet-based empirical Wiener filter and wavelet-based total variation (WATV) to denoise adventitious lung sound signals. As an optimal filter, the waveletbased empirical Wiener filter requires appropriate selections of two wavelet transform bases, whereas WATV indirectly eliminates the need to select the wavelet transform bases by modifying a single objective function to achieve a minimax optimal filter in the sense of mean-squared error. We combined the two approaches by using the improved signal estimation from WATV to design an empirical Wiener filter for suppressing noise and smoothing the denoised signal. The performance of our proposed technique is evaluated via root-mean-squared error (RMSE) and signal-to-noise ratio (SNR) on simulated lung sound containing crackle and wheeze transmitted out of the chest wall and being corrupted with white Gaussian noise at various power levels. In simulation studies, our proposed technique achieved optimal RMSE similarly to the WATV filter accomplishes as an optimal filter-not only preserving signal characteristics but also further improving SNR by 6-9 dB compared to the wavelet soft and hard threshold functions, total variation denoising filter and the WATV filter. Additionally, our proposed technique is less sensitive to the variation of SNR values of the input signal.

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Modeling and Simulation of Pulmonary Acoustic Signal and Imaging for Lung Function Assessment

2023 IEEE International Conference on Consumer Electronics (ICCE), Jan 6, 2023

Selecting Efficient Parameters Thresholds for a Hybrid Wavelet-based Total Variation and Wiener Filter for Denoising Lung Sound Signals

<title>Detection and suppression for mechanical resonance in hard disk drives with built-in piezoelectric sensors</title>

Proceedings of SPIE, Jul 1, 2002

Many components in hard disk drives (HDDs), when in operation, are subjected to vibration due to ... more Many components in hard disk drives (HDDs), when in operation, are subjected to vibration due to out of balance of rotating components, inertial impacts under servo driving and dynamic interactions between components. These vibrations have been found to have significant effect upon the servo performance of drive systems. In order to improve the servo performance by reducing the effect of mechanical resonance in HDDs, this paper seeks to detect and suppress mechanical resonance of the head actuator using smart sensors and multi-sensing control techniques. In this regard, sensitive and miniature piezoelectric elements from the polymer-based piezoelectric materials PVDF (polyvinylindin fluoride) or the ceramic-based piezoelectric materials PZT 9lead zircornate titanate) are built in the head actuator for sensing the mechanical vibration. In the experiment, the multi-sensing signals by the piezoelectric sensors and the laser Doppler vibrometer (LDV) are transferred into a voice coil motor (VCM) through a feedback controller so as to actively suppress structural resonance. Numerical simulation and experimental results indicate that the piezoelectric sensors provide an effective way in monitoring the HDD actuator resonance, and the active vibration control strategy is capable of suppressing main mechanical resonance in the head actuator effectively.

A piezoelectric micro-actuator with a three-dimensional structure and its micro-fabrication

Sensors and Actuators A-physical, Aug 1, 2006

Piezoelectric micro-actuators are promising for applications in various servo control systems, wi... more Piezoelectric micro-actuators are promising for applications in various servo control systems, with the potential to provide ultra-precision positioning and compensation. In this paper, a micro-actuator, which is configured with an “H-shaped” cavity and a pair of high aspect ratio parallel beams, was designed. The micro-actuator with the three-dimensional structure is capable of providing in-plane flexibility and out-of-plane stiffness. Appropriate material

Critical implementation issues in compensation for nonlinearities in industrial robot manipulators by adaptive multilayer neural networks

... Yaolong Lou*, Joachim Holtz** and T. H. Lee* *Department of Electrical Engineering, National ... more

Restoration of Lung Sound Signals Using a Hybrid Wavelet-Based Approach

IEEE Sensors Journal, Oct 15, 2022

A unique and ideal integration of wavelet-based total variation (WATV) and empirical Wiener denoi... more A unique and ideal integration of wavelet-based total variation (WATV) and empirical Wiener denoising method is proposed in this paper to significantly enhance the signal-tonoise ratio (SNR) while preserving the characteristics of a lung sound signal. While individual wavelet-based denoising filters based on a single basis function have been employed in the past, the outcome has been unsatisfactory because only significant (signal) wavelet coefficients are considered for denoising analysis. The new WATV-Wiener hybrid technique, proposed here, takes into account both significant and insignificant (noise) wavelet coefficients of the noisy signal. An intensive analysis of selecting and fine-tuning the WATV-Wiener filter parameters is presented here through the simulation studies. The WATV-Wiener filter applied here onto different one-dimensional lung sound signals of different noise levels has led to an optimal root mean square error compared to seven other state-of-the-art filters reported in the literature. The optimal parameters achieved through our simulation studies led to a 3-20 dB improvement in SNR, and the average SNR was improved by 4-30 dB in our experiment. We also observed that the WATV-Wiener filter is less sensitive to the variation of SNR values of the input signal. Furthermore, the WATV-Wiener filter obtains similar SNR performance between continuous piecewise signal (wheeze) and noncontinuous piecewise signal (crackle) in both simulation and experimental studies.

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Acoustic Lung Imaging Utilized in Continual Assessment of Patients with Obstructed Airway: A Systematic Review

Sensors

Smart respiratory therapy is enabled by continual assessment of lung functions. This systematic r... more Smart respiratory therapy is enabled by continual assessment of lung functions. This systematic review provides an overview of the suitability of equipment-to-patient acoustic imaging in continual assessment of lung conditions. The literature search was conducted using Scopus, PubMed, ScienceDirect, Web of Science, SciELO Preprints, and Google Scholar. Fifteen studies remained for additional examination after the screening process. Two imaging modalities, lung ultrasound (LUS) and vibration imaging response (VRI), were identified. The most common outcome obtained from eleven studies was positive observations of changes to the geographical lung area, sound energy, or both, while positive observation of lung consolidation was reported in the remaining four studies. Two different modalities of lung assessment were used in eight studies, with one study comparing VRI against chest X-ray, one study comparing VRI with LUS, two studies comparing LUS to chest X-ray, and four studies comparin...

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Modeling and Simulation of Pulmonary Acoustic Signal and Imaging for Lung Function Assessment

2023 IEEE International Conference on Consumer Electronics (ICCE)

Selecting Efficient Parameters Thresholds for a Hybrid Wavelet-based Total Variation and Wiener Filter for Denoising Lung Sound Signals

2022 6th International Conference on Imaging, Signal Processing and Communications (ICISPC)

Restoration of Lung Sound Signals Using a Hybrid Wavelet-Based Approach

IEEE Sensors Journal

A unique and ideal integration of wavelet-based total variation (WATV) and empirical Wiener denoi... more A unique and ideal integration of wavelet-based total variation (WATV) and empirical Wiener denoising method is proposed in this paper to significantly enhance the signal-tonoise ratio (SNR) while preserving the characteristics of a lung sound signal. While individual wavelet-based denoising filters based on a single basis function have been employed in the past, the outcome has been unsatisfactory because only significant (signal) wavelet coefficients are considered for denoising analysis. The new WATV-Wiener hybrid technique, proposed here, takes into account both significant and insignificant (noise) wavelet coefficients of the noisy signal. An intensive analysis of selecting and fine-tuning the WATV-Wiener filter parameters is presented here through the simulation studies. The WATV-Wiener filter applied here onto different one-dimensional lung sound signals of different noise levels has led to an optimal root mean square error compared to seven other state-of-the-art filters reported in the literature. The optimal parameters achieved through our simulation studies led to a 3-20 dB improvement in SNR, and the average SNR was improved by 4-30 dB in our experiment. We also observed that the WATV-Wiener filter is less sensitive to the variation of SNR values of the input signal. Furthermore, the WATV-Wiener filter obtains similar SNR performance between continuous piecewise signal (wheeze) and noncontinuous piecewise signal (crackle) in both simulation and experimental studies.

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Compensation for nonlinearities in robot manipulators by on-line learning multilayer neural networks

Frequency-Adaptive Notch Filter

Robust triple-mode compensator for hard disk drives with dynamic friction

US6937430Granted Paten

Improving the performance of industrial robot manipulators by neural networks

Proceedings of IECON'94 - 20th Annual Conference of IEEE Industrial Electronics

Robot manipulators are nonlinear systems. Centrifugal and Coriolis forces as well as the influenc... more Robot manipulators are nonlinear systems. Centrifugal and Coriolis forces as well as the influence of gravitation and friction depend on the state variables of the system. In the presence of strong nonlinearities, linear PID controllers for the individual joint axis drives, usually employed in industrial applications, cannot provide satisfactory performance due to their inherent limitations. Model-based schemes have the disadvantage that they require accurate system models, which are difficult to obtain. The problem is solved by using multilayer feedforward neural networks, which do not rely on a system model. They are used as an addition to the existing linear individual joint control structure. The convergence of the system is proved using Lyapunov's stability theory. Experiments obtained on a two-degree-of-freedom manipulator demonstrate the effectiveness of the proposed technique

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