Chronic respiratory diseases are diseases of the airways and other structures of the lung, usually resulting in difficulty in breathing and other symptoms. Chronic obstructive pulmonary disease (COPD) is considered to be one of the most common of respiratory diseases. Nowadays, spirometry remains the golden standard for diagnosing and staging COPD. By taking into consideration the possibility of this disease worsening over time and its negative impact on patient's life, sufferers should conduct regular spirometry checks at medical centers or buy expensive and portable devices to monitor and manage the disease. Therefore, COPD spirometry is costly in terms of both, money and time. In this work and due to the pervasiveness and advancement of smartphones, we attempt to make use of their built-in sensors and ever increasing computational capabilities to provide patients with a mobile based spirometer capable of diagnosing and managing COPD in a reliable and cost effective manner. We develop a model that allows the computation of the two critical parameters FVC and FEV1 by establishing a relationship between the frequency response of human exhalation recorded by mobile microphone and the actual flow rate. These two parameters are critical in diagnosing COPD. Preliminary results show that the mean percent error between FVC, FEV1, and FEV1/FVC ratio data as computed using MobSpiro application and the clinical spirometer is 4.6%, 3.1%, and 3.5% respectively. These results prove the effectiveness of the proposed system when compared to the clinical spirometer, and confirm that smartphones can play an important role in healthcare in the coming future.

MobSpiro: Mobile based spirometry for detecting COPD

This paper focuses on respiratory phase detection and classification without the help of the airflow measurements. Instead of using the airflow measurements to identify breathing phases, the proposed work depends on advanced digital signal processing techniques to process the acoustic signal of respiration that was collected using a microphone placed in front of the subject's nose. The recorded signal is processed using the voiced-unvoiced algorithm to differentiate between the voiced period and the unvoiced (silence) period. The desired features are extracted from each voiced phase. Finally, support vector machine is used to distinguish between the inspiration and the expiration phases according to the extracted features. The signals were recorded from a number of subjects who do not have a history of pulmonary diseases. The proposed method has achieved an accuracy of 95% when tested on the subjects.

Automatic detection and classification of acoustic breathing cycles

Virtual reality for COPD rehabilitation: a technological perspective.

Devices, system, and methods generate expiratory flow-based pulmonary function data by processing a digital audio file of sound of a subject's forced expiratory maneuver. A mobile device configured to generate expiratory flow-based pulmonary function data includes a microphone, a processor, and a data storage device. The microphone is operable to convert sound of the subject's forced expiratory maneuver into a digital data file. The processor is operatively coupled with the microphone. The data storage device is operatively coupled with the processor and stores instructions that, when executed by the processor, cause the processor to process the digital data file to generate expiratory flow-based pulmonary function data for assessing pulmonary function of the subject. The sound of the subject's forced expiratory maneuver can be converted into the digital data file without contact between the subject's mouth and the mobile device.

Sound-based spirometric devices, systems and methods

Chronic Obstructive Pulmonary Disease (COPD) refers to a collection of lung diseases that result in breathing difficulties. In some cases, the symptoms of COPD can be reduced, by engaging in breathing exercises. Technology can support, and we are developing AirFlow, a suite of interactive computer games, to guide breathing exercises and promote learning. To establish requirements, we interviewed 20 people with COPD, in China, to understand their use of breathing exercises, and learn how technology might fit their lifestyle. The findings informed our design goals. We outline a prototype system, where respiration rate, waveform, and amplitude are captured and used to control a virtual environment. The system will guide users through breathing exercises, and provide training instructions, using a series of games. The immersive environment aims to support a fun and motivating experience, therefore underpinning user confidence.

AirFlow: designing immersive breathing training games for COPD

COPD (Chronic Obstructive Pulmonary Disease) is a serious lung disease that causes difficulty in breathing. COPD patients require lung function examinations and perform breathing exercises on a regular basis in order to manage and be more aware of their health status. In this paper, we designed and developed a mobile-phone based system for lung function diagnosis, called mCOPD. Besides enabling accurate COPD examinations at home, the mCOPD system also offers a video-game based guidance system for breathing exercises. We evaluated mCOPD in controlled and uncontrolled environments with 40 subjects. The experimental results show that our system is a promising tool for remote medical treatment of COPD.

/pdf/mcopd-mobile-phone-based-lung-function-diagnosis-and-ryl0hu41ee.pdf

mCOPD: mobile phone based lung function diagnosis and exercise system for COPD

Silk fibroin (SF) is a structural protein derived from natural silkworm silks. Materials fabricated based on SF usually inherit extraordinary physical and biological properties, including high mechanical strength, toughness, optical transparency, tailorable biodegradability, and biocompatibility. Therefore, SF has attracted interest in the development of sustainable biodevices, especially for emergent bio-electronic technologies. To expand the function of current silk devices, the SF characteristic sequence has been used to synthesize recombinant silk proteins that benefit from SF and other functional peptides, such as stimuli-responsive elastin peptides. In addition to genetic engineering methods, innovated chemistry modification approaches and improved material processing techniques have also been developed for fabricating advanced silk materials with tailored chemical features and nanostructures. Herein, this review summarizes various methods to synthesize functional silk-based materials from different perspectives. This review also highlights the recent advances in the applications of natural and recombinant silks in tissue regeneration, soft robotics, and biosensors, using B. mori SF and silk-elastin-like proteins (SELPs) as examples.

Engineering Natural and Recombinant Silks for Sustainable Biodevices

In the new era of China, the communication modality has undergone great changes. Therefore, the dissemination of Marxism in colleges and universities must adapt to the requirements of the new period. In fact, the channels of ideological and political education have shifted to some extent from the traditional dissemination of teachers' lectures and textbooks to the modern one of media convergence such as fast news and short videos.

/pdf/a-study-on-marxism-dissemination-in-chinese-colleges-and-16beazer.pdf

Xinchen Shen

Papers

mCOPD: mobile phone based lung function diagnosis and exercise system for COPD

Engineering Natural and Recombinant Silks for Sustainable Biodevices

A study on marxism dissemination in chinese colleges and universities in the new era