Qiang Pan

Bio: Qiang Pan is an academic researcher from University of Toulouse. The author has contributed to research in topics: Sleep (system call) & Polysomnography. The author has an hindex of 2, co-authored 4 publications receiving 10 citations.

Current Status and Future Challenges of Sleep Monitoring Systems: Systematic Review

Abstract: Background: Sleep is essential for human health. Considerable effort has been put into academic and industrial research and in the development of wireless body area networks for sleep monitoring in terms of nonintrusiveness, portability, and autonomy. With the help of rapid advances in smart sensing and communication technologies, various sleep monitoring systems (hereafter, sleep monitoring systems) have been developed with advantages such as being low cost, accessible, discreet, contactless, unmanned, and suitable for long-term monitoring. Objective: This paper aims to review current research in sleep monitoring to serve as a reference for researchers and to provide insights for future work. Specific selection criteria were chosen to include articles in which sleep monitoring systems or devices are covered. Methods: This review investigates the use of various common sensors in the hardware implementation of current sleep monitoring systems as well as the types of parameters collected, their position in the body, the possible description of sleep phases, and the advantages and drawbacks. In addition, the data processing algorithms and software used in different studies on sleep monitoring systems and their results are presented. This review was not only limited to the study of laboratory research but also investigated the various popular commercial products available for sleep monitoring, presenting their characteristics, advantages, and disadvantages. In particular, we categorized existing research on sleep monitoring systems based on how the sensor is used, including the number and type of sensors, and the preferred position in the body. In addition to focusing on a specific system, issues concerning sleep monitoring systems such as privacy, economic, and social impact are also included. Finally, we presented an original sleep monitoring system solution developed in our laboratory. Results: By retrieving a large number of articles and abstracts, we found that hotspot techniques such as big data, machine learning, artificial intelligence, and data mining have not been widely applied to the sleep monitoring research area. Accelerometers are the most commonly used sensor in sleep monitoring systems. Most commercial sleep monitoring products cannot provide performance evaluation based on gold standard polysomnography. Conclusions: Combining hotspot techniques such as big data, machine learning, artificial intelligence, and data mining with sleep monitoring may be a promising research approach and will attract more researchers in the future. Balancing user acceptance and monitoring performance is the biggest challenge in sleep monitoring system research.

Design of a Smart Sole with Advanced Fall Detection Algorithm

Abstract: Fall has become the second leading cause of unintentional injury, death, after road traffic injuries, for the elderly in Europe. This proportion will increase in the next decades and become more than ever a real public health issue. France was selected by the World Health Organization to be the first country to implement a program that reduces the coverage of the dependence. Commercial automatic fall detection devices can help seniors get back on their feet faster by reducing the time of emergency procedure. Many seniors do not take advantage of this potentially life-saving technology mainly because of intrusiveness constraints. After having reminded the context and the challenges of fall detection systems, this paper presents an original device which is unobtrusive, comfortable and very effective. The hardware architecture embedded into the sole and a new fall detection algorithm based on acceleration and time thresholds are presented. The algorithm introduces a new concept of differential acceleration to eliminate some drawbacks of current systems. Tests were carried out under real life conditions by 6 young participants for different ADLs. The data were analyzed blindly. We compared the detected falls and found a 100% sensibility and more than 93% sensitivity for all participants and scenarios.

Preparation of glycosyl carboxylic acids via stereoselective synthesis and oxidative cleavage of C-vinyl glycosides.

Abstract: We have developed an improved cyanide-free strategy for the synthesis of glycosyl carboxylic acids, employing stereoselective C-vinyl glycosylation and oxidative cleavage of C-vinyl glycosides as key steps. Compared to our previous work, the amount of NaIO4 required for the oxidative cleavage step is reduced significantly from 18 equivalents to 4.5 equivalents. This modification not only is advantageous in terms of operation and costs but also avoids the over-oxidation problem, thus greatly expanding the substrate scope, which is evidenced by the fact that 10 out of 21 glycosyl carboxylic acids synthesized are undocumented. With differently O5-protected furanosyl acids in hand, we demonstrate that an electron-rich protecting group is beneficial for the decarboxylative arylation of furanosyl carboxylic acids. This represents a rare example of protecting groups affecting the reaction efficiency in radical C-glycosylation. As C-vinyl glycosides can be prepared stereoselectively and the oxidative step is stereoretentive, the approach provides an effective means to access 1,2-trans or 1,2-cis glycosyl acids, which would be a valuable alternative to the cyanide-based synthesis of glycosyl carboxylic acids.

Wrist movement analysis for long-term home sleep monitoring

Abstract: In this paper, we present several original methods for classifying sleep stages, including threshold based and k-means clustering based methods. The proposed algorithms use only acceleration data from non-dominant wrist, resulting in a classification into 4-sleep stages (“awake”, “light sleep”, “deep sleep” and “REM (Rapid eye movement)”) for overnight sleep. We validate our methods by referring to the results of “Fitbit” and subjective feedbacks from volunteers on quality of sleep. Our algorithms compute the duration of each sleep stage to evaluate changes in sleep quality between different nights. A method of calculating a sleep score based on the duration of sleep and the duration of each sleep stage is proposed, which facilitates the evaluation of sleep quality by a single score. 5 volunteers were recruited for the tests. Among all the test nights, the proposed algorithm based on k-means clustering shows a superior or equivalent performance compared to the “Fitbit” results. These promising results allow us to consider a new non-intrusive method for users and medical staff to monitor the evolution of sleep quality through long-term follow-up. In addition, to evaluate the performance of our proposed system in terms of sleep stage classification, we use the PSG (Polysomnography) sleep monitoring gold standard to monitor the sleep of one of the volunteers throughout the night in a hospital’s professional sleep laboratory. This experiment shows that the proposed 5 km2 (5 iterations of k-means clustering with k = 2) method and the threshold method are in good agreement with the PSG results. The accuracy of awake, REM, light sleep and deep sleep detection reaches respectively 0.78, 0.96, 0.75 and 0.97 by the Threshold method. More specifically, both methods we propose show good performance in the detection of awake and deep sleep. This longitudinal monitoring can help to detect abnormal changes in sleep that are usually a sign of a change in health status.

Elderly Fall Detection Systems: A Literature Survey

Abstract: Falling is among the most damaging event elderly people may experience. With the ever-growing aging population, there is an urgent need for the development of fall detection systems. Thanks to the rapid development of sensor networks and the Internet of Things (IoT), human-computer interaction using sensor fusion has been regarded as an effective method to address the problem of fall detection. In this paper, we provide a literature survey of work conducted on elderly fall detection using sensor networks and IoT. Although there are various existing studies which focus on the fall detection with individual sensors, such as wearable ones and depth cameras, the performance of these systems are still not satisfying as they suffer mostly from high false alarms. Literature shows that fusing the signals of different sensors could result in higher accuracy and lower false alarms, while improving the robustness of such systems. We approach this survey from different perspectives, including data collection, data transmission, sensor fusion, data analysis, security, and privacy. We also review the benchmark data sets available that have been used to quantify the performance of the proposed methods. The survey is meant to provide researchers in the field of elderly fall detection using sensor networks with a summary of progress achieved up to date and to identify areas where further effort would be beneficial.

Atlas of Sleep Medicine

Abstract: Atlas of Sleep Medicine by Sudhansu Chokroverty, Robert J. Thomas, and Meeta Bhatt, 376 pp., Elsevier, 2005, $99.00 In contrast, the Atlas of Sleep Medicine is an atlas of polysmonographic studies. It goal is to introduce the basics of polysomnography. The first part of the atlas reviews electroencephalography, scoring sleep stages and …

A comprehensive review on the prospects of next-generation wearable electronics for individualized health monitoring, assistive robotics, and communication

Abstract: Wearable electronics offer a robust and emerging framework for invasive and on-skin electronics that are expected to be long-lasting, lightweight, flexible, and conformable. Critical health data monitoring, such as body temperature, wrist pulse, and blood glucose, can be retrieved and evaluated using next-generation electronic devices fabricated with advanced materials and innovative strategies. Over the past years, these devices have revealed an unprecedented transformation in a variety of other applications, including smart prosthetics, assistive robotics, energy harvesting and storage, display sensors, defense, and so forth. Here, we review the latest advancements in wearable electronics, focusing on three significant areas, including (Ⅰ) personalized health monitoring that enables the recording of several physiological and biochemical signals, (Ⅱ) assistive robotics and prosthetics for limb movements and realizing pain or touch sensations to enable disabled patients, while performing their daily tasks (Ⅲ) information and communication, which includes infrared (IR) sensing and holograms. The categorization of wearable electronics such as mountable, textile-based, implantable, and skin-like electronics are briefly summarized. Furthermore, this review provides in-depth insights into the opportunities and constraints for designing next-generation wearable electronics. As a result, this study includes a thorough introduction, overview, limitations and future prospects of wearable electronics, making it a valuable resource for advancing the development of future electronics.

Technological Requirements and Challenges in Wireless Body Area Networks for Health Monitoring: A Comprehensive Survey

Abstract: With the rapid growth in healthcare demand, an emergent, novel technology called wireless body area networks (WBANs) have become promising and have been widely used in the field of human health monitoring. A WBAN can collect human physical parameters through the medical sensors in or around the patient’s body to realize real-time continuous remote monitoring. Compared to other wireless transmission technologies, a WBAN has more stringent technical requirements and challenges in terms of power efficiency, security and privacy, quality of service and other specifications. In this paper, we review the recent WBAN medical applications, existing requirements and challenges and their solutions. We conducted a comprehensive investigation of WBANs, from the sensor technology for the collection to the wireless transmission technology for the transmission process, such as frequency bands, channel models, medium access control (MAC) and networking protocols. Then we reviewed its unique safety and energy consumption issues. In particular, an application-specific integrated circuit (ASIC)-based WBAN scheme is presented to improve its security and privacy and achieve ultra-low energy consumption.

Non-invasive Techniques for Monitoring Different Aspects of Sleep: A Comprehensive Review

Abstract: Quality sleep is very important for a healthy life. Nowadays, many people around the world are not getting enough sleep, which has negative impacts on their lifestyles. Studies are being conducted for sleep monitoring and better understanding sleep behaviors. The gold standard method for sleep analysis is polysomnography conducted in a clinical environment, but this method is both expensive and complex for long-term use. With the advancements in the field of sensors and the introduction of off-the-shelf technologies, unobtrusive solutions are becoming common as alternatives for in-home sleep monitoring. Various solutions have been proposed using both wearable and non-wearable methods, which are cheap and easy to use for in-home sleep monitoring. In this article, we present a comprehensive survey of the latest research works (2015 and after) conducted in various categories of sleep monitoring, including sleep stage classification, sleep posture recognition, sleep disorders detection, and vital signs monitoring. We review the latest research efforts using the non-invasive approach and cover both wearable and non-wearable methods. We discuss the design approaches and key attributes of the work presented and provide an extensive analysis based on ten key factors, with the goal to give a comprehensive overview of the recent developments and trends in all four categories of sleep monitoring. We also collect publicly available datasets for different categories of sleep monitoring. We finally discuss several open issues and future research directions in the area of sleep monitoring.