Background: Articular cartilage has a zonal architecture and biphasic mechanical properties. The recapitulation of surface lubrication properties with high compressibility of the deeper layers of articular cartilage during regeneration is essential in achieving long-term cartilage integrity. Current clinical approaches for cartilage repair, especially with the use of mesenchymal stem cells (MSCs), have yet to restore the hierarchically organized architecture of articular cartilage. Hypothesis: MSCs predifferentiated on surfaces with specific nanotopographic patterns can provide phenotypically stable and defined chondrogenic cells and, when delivered as a bilayered stratified construct at the cartilage defect site, will facilitate the formation of functionally superior cartilage tissue in vivo. Study Design: Controlled laboratory study. Methods: MSCs were subjected to chondrogenic differentiation on specific nanopatterned surfaces. The phenotype of the differentiated cells was assessed by the expression of cartilage markers. The ability of the 2-dimensional nanopattern-generated chondrogenic cells to retain their phenotypic characteristics after removal from the patterned surface was tested by subjecting the enzymatically harvested cells to 3-dimensional fibrin hydrogel culture. The in vivo efficacy in cartilage repair was demonstrated in an osteochondral rabbit defect model. Repair by bilayered construct with specific nanopattern predifferentiated cells was compared with implantation with cell-free fibrin hydrogel, undifferentiated MSCs, and mixed-phenotype nanopattern predifferentiated MSCs. Cartilage repair was evaluated at 12 weeks after implantation. Results: Three weeks of predifferentiation on 2-dimensional nanotopographic patterns was able to generate phenotypically stable chondrogenic cells. Implantation of nanopatterned differentiated MSCs as stratified bilayered hydrogel constructs improved the repair quality of cartilage defects, as indicated by histological scoring, mechanical properties, and polarized microscopy analysis. Conclusion: Our results indicate that with an appropriate period of differentiation, 2-dimensional nanotopographic patterns can be employed to generate phenotypically stable chondrogenic cells, which, when implanted as stratified bilayered hydrogel constructs, were able to form functionally superior cartilage tissue. Clinical Relevance: Our approach provides a relatively straightforward method of obtaining large quantities of zone-specific chondrocytes from MSCs to engineer a stratified cartilage construct that could recapitulate the zonal architecture of hyaline cartilage, and it represents a significant improvement in current MSC-based cartilage regeneration.

A unique and ideal integration of wavelet-based total variation (WATV) and empirical Wiener denoising method is proposed in this article to significantly enhance the signal-to-noise 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 wavelet-based empirical Wiener (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 1-D lung sound signals of different noise levels has led to an optimal root mean square error (RMSE) compared with 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.

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.

Lung sounds can be translated into acoustic imaging as an alternative to standard imaging to assess lung function frequently for improved therapy efficiency. This study proposes a comprehensive acoustic lung imaging system translated from acquired lung sounds for continual and reliable lung function assessment in response to the growing clinical interest in frequent lung function assessment. The proposed system comprises sub-systems such as data acquisition, signal processing and imaging algorithm. This study demonstrated the design and implementation of a robust lung sound acquisition and imaging system using microelectromechanical microphones that reduce external noise contamination through redesigned hardware and dynamic signal processing. Regarding lung signal acquisition, the proposed system accomplished better root mean square error (RMSE) by around 0.15 and signal-to-noise ratio (SNR) by about 7 dB compared to commercial digital stethoscopes. RMSE and SNR reflect the accuracy in capturing desired signals and robustness to noise contamination and are used to quantitatively compare the system data acquisition to commercially available acoustic and electronic devices in a noisy setting. The proposed system sensors’ position is neutral when representing lung signals, with a signal power loss ratio of around 5 dB compared to 10 dB from digital stethoscopes, in terms of sensor sensing sensitivity power spectrum mapping. The proposed system obtains about 7% to 12% more accurate detection of the actual nidus length than digital stethoscopes through imaging translated from acquired lung signals. Additionally, the detected airway obstruction results agree closely (91%) with airway remodeling studies.

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 comparing LUS in contrast to computed tomography. Our findings indicate that the acoustic imaging approach could assess and provide regional information on lung function. No technology has been shown to be better than another for measuring obstructed airways; hence, more research is required on acoustic imaging in detecting obstructed airways regionally in the application of enabling smart therapy.

High-frequency chest wall oscillation (HFCWO) therapy is one of the techniques to facilitate the draining of a patient’s lung secretion in pathological situations, and smart therapy with HFCWO devices equipped with multiple actuators can be achieved via locating nidi in the lung. In this paper, through developing a novel acoustic lung spatial model and utilizing acoustic imaging simulation, a new and effective method for assessing lung function with acoustic imaging is presented, which links acoustic lung images with pathologic changes. The structural similarity between the acoustic reference image based on actual lung sound and our model acoustic image based on the airway impedance was achieved by an index of 0.8987, with 1 as the exact score. Simulation studies based on the model are used to analyze the practicality and the extreme design of the acoustic imaging system on the resolution of the located nidus. For instance, a practical system design with sensor numbers between 4 and 35 may recognize a lower resolution nidus length of 73 mm to a better resolution nidus length of 22 mm. On the other hand, an extreme system design with more than 1000 sensors can recognize greater nidus resolution at under 10 mm. Additionally, this research may be utilized to offer recommendations for acoustic imaging system design and assess the number of sensors and sensing diameter in current acoustic imaging systems. Furthermore, the geographic detection of nidus length allows for analyzing of HFCWO therapy results.