Wearing masks has been a recommended protective measure due to the risks of coronavirus disease 2019 (COVID-19) even in its coming endemic phase. Therefore, deploying a "smart mask" to monitor human physiological signals is highly beneficial for personal and public health. This work presents a smart mask integrating an ultrathin nanocomposite sponge structure-based soundwave sensor (≈400 μm), which allows the high sensitivity in a wide-bandwidth dynamic pressure range, i.e., capable of detecting various respiratory sounds of breathing, speaking, and coughing. Thirty-one subjects test the smart mask in recording their respiratory activities. Machine/deep learning methods, i.e., support vector machine and convolutional neural networks, are used to recognize these activities, which show average macro-recalls of ≈95% in both individual and generalized models. With rich high-frequency (≈4000 Hz) information recorded, the two-/tri-phase coughs can be mapped while speaking words can be identified, demonstrating that the smart mask can be applicable as a daily wearable Internet of Things (IoT) device for respiratory disease identification, voice interaction tool, etc. in the future. This work bridges the technological gap between ultra-lightweight but high-frequency response sensor material fabrication, signal transduction and processing, and machining/deep learning to demonstrate a wearable device for potential applications in continual health monitoring in daily life.

Background Syndrome differentiation is a commonly used methodology and practice in Traditional Chinese Medicine (TCM) guiding the diagnosis and treatment of diseases including heart failure (HF). However, previous clinical trials seldom consider the impact of syndrome patterns on the outcome evaluation of TCM formulae. Qiliqiangxin (QLQX) capsule is a TCM formula with cardiotonic effect to improve the cardiovascular function for heart failure with proven efficacy from well-designed clinical trials. Though, there is no clinical trial with a large sample size and long assessment period that considers the relationship between TCM syndrome differentiation and the treatment efficacy of QLQX. In the present study, we design a study protocol to evaluate the relationship between TCM syndrome differentiation and the severity of heart failure as well as its progression. Furthermore, we will evaluate the impact of the TCM syndrome patterns on the efficacy of QLQX in the outcome of heart failure. Methods This is a clinical study conducted in conjunction with an ongoing clinical trial (QUEST Study) by sharing the parent patient populations but with different aims and independent designed roadmaps to investigate the TCM syndrome pattern distributions and the impacts of syndrome pattern types on the efficacy of QLQX in HF treatment. The clinical trial involves over 100 hospitals in mainland China and Hong Kong SAR with 3080 HF patients. By assessing the morbidity and re-hospitalization, we will verify and apply a modified TCM Questionnaire to collect the clinical manifestations of HF and acquire the tongue images of the patients to facilitate the syndrome differentiation. We will base on the “2014 Consensus from TCM experts on diagnosis and treatment of chronic heart failure” to evaluate the TCM syndromes for the patients. A pilot study with at least 600 patients will be conducted to evaluate the reliability, feasibility and validity of the modified TCM questionnaire for syndrome differentiation of HF and the sample size is calculated based on the confidence level of 95%, population size of 3080 and 5% margin of error. Secondly, we will investigate the characteristic of TCM syndrome distribution of HF patients and its correlation with the functional and biochemical data. Furthermore, we will evaluate the relationship between the TCM syndrome patterns and the efficacy of QLQX in the treatment of heart failure. Lastly, we will investigate the implication of tongue diagnosis in the severity and therapeutic outcome of HF. Expect outcomes To our knowledge, this is the first large scale clinical trial to evaluate the impacts of TCM syndrome differentiation on the progression and therapeutic outcome of HF patients and explore the diagnostic value of TCM Tongue Diagnosis in HF patients. We expect to obtain direct clinical evidence to verify the importance of TCM syndrome differentiation for the diagnosis and treatment of HF. Trial Registration: The trial was registered at Chinese Clinical Trial Registry, http://www.chictr.org.cn. (Registration No.: ChiCTR1900021929); Date: 2019-03-16.

Background Traditional Chinese Medicine (TCM) is widely used to treat heart failure (HF). Syndrome differentiation is a unique and crucial component in TCM practice for guiding disease diagnosis and treatment strategies as well as clinical research. The major bottlenecks in TCM syndrome differentiation are the diversity of the syndrome differentiation criteria and the broad spectrum of syndrome patterns, hindering evidence-based studies for clinical research. In the present study, we aim to develop an evidence-based questionnaire for the diagnosis of HF and establish a definitive set of criteria for syndrome differentiation. Methods We designed a TCM syndrome differentiation questionnaire for heart failure (SDQHF) based on the "TCM expert consensus for diagnosis and treatment of heart failure" (expert consensus), literature review, and various clinical guidelines. To test the reliability and efficiency of the questionnaire, we performed a large-scale multiple-center clinical trial with the recruitment of 661 HF patients. Cronbach's alpha was used to assess the internal consistency of the SDQHF. Content validity was conducted through expert review. Principal component analysis (PCA) was applied to evaluate the construct validity. We constructed a proposed model for syndrome differentiation for HF based on the PCA results. Tongue analysis was performed to verify the accuracy of syndromes derived from the proposed model and the expert consensus. An evidence-based practical questionnaire for TCM syndrome differentiation patients was developed and validated with the data from 661 HF patients. Results The syndrome differentiation criteria were constructed with five syndrome elements (qi-deficiency, yang-deficiency, yin-deficiency, blood stasis, and phlegm retention). The results revealed good convergent and discriminant validity, satisfactory internal consistency, and feasibility. The significant discoveries include: (1) A total of 91% of the derived TCM syndromes from the proposed model matched with the characterized tongue images of the syndrome patterns; (2) Qi Deficiency Syndrome is the dominant syndrome pattern for HF patients, followed by Yang-Qi Deficiency Syndrome and Qi-yin deficiency Syndrome, and finally, Yin-Yang Dual Deficiency Syndrome; (3) The majority of the HF patients had the combination of Blood Stasis and Phlegm Retention Syndromes; (4) The "Yin-Yang Dual Deficiency" Syndrome was a valid syndrome for HF, suggesting that this syndrome pattern should be included in the criteria for syndrome differentiation; and (5) Through the validation of the expert consensus, several recommendations were proposed to improve the accuracy of syndrome differentiation of HF. Conclusions The proposed SDQHF and the criteria could be a reliable and valid tool for syndrome differentiation of heart failure with high accuracy. It is recommended to use the proposed model for evidence-based study on Chinese Medicine to diagnose and treat HF. Trial registration number: The trial was registered at the Chinese Clinical Trial Registry, http://www.chictr.org.cn. (Registration No.: ChiCTR1900021929); Date: 2019-03-16.