ABSTRACT
Sleep is crucial for human health from metabolic, mental, emotional, and social points of view; obtaining good sleep in terms of quality and duration is fundamental for maintaining a good life quality. Over the years, several systems have been proposed in the scientific literature and on the market to derive metrics used to quantify sleep quality as well as detect sleep disturbances and disorders. In this field, wearable systems have an important role in the discreet, accurate, and long-term detection of biophysical markers useful to determine sleep quality. This paper presents the current state-of-the-art wearable systems and software tools for sleep staging and detecting sleep disorders and dysfunctions. At first, the paper discusses sleep's functions and the importance of monitoring sleep to detect eventual sleep disturbance and disorders. Afterward, an overview of prototype and commercial headband-like wearable devices to monitor sleep is presented, both reported in the scientific literature and on the market, allowing unobtrusive and accurate detection of sleep quality markers. Furthermore, a survey of scientific works related the effect of the COVID-19 pandemic on sleep functions, attributable to both infection and lifestyle changes. In addition, a survey of algorithms for sleep staging and detecting sleep disorders is introduced based on an analysis of single or multiple biosignals (EEG-electroencephalography, ECG-electrocardiography, EMG-electromyography, EOG-electrooculography, etc.). Lastly, comparative analyses and insights are provided to determine the future trends related to sleep monitoring systems.
ABSTRACT
The demand for wearable devices to measure respiratory activity is constantly growing, finding applications in a wide range of scenarios (e.g., clinical environments and workplaces, outdoors for monitoring sports activities, etc.). Particularly, the respiration rate (RR) is a vital parameter since it indicates serious illness (e.g., pneumonia, emphysema, pulmonary embolism, etc.). Therefore, several solutions have been presented in the scientific literature and on the market to make RR monitoring simple, accurate, reliable and noninvasive. Among the different transduction methods, the piezoresistive and inertial ones satisfactorily meet the requirements for smart wearable devices since unobtrusive, lightweight and easy to integrate. Hence, this review paper focuses on innovative wearable devices, detection strategies and algorithms that exploit piezoresistive or inertial sensors to monitor the breathing parameters. At first, this paper presents a comprehensive overview of innovative piezoresistive wearable devices for measuring user’s respiratory variables. Later, a survey of novel piezoresistive textiles to develop wearable devices for detecting breathing movements is reported. Afterwards, the state-of-art about wearable devices to monitor the respiratory parameters, based on inertial sensors (i.e., accelerometers and gyroscopes), is presented for detecting dysfunctions or pathologies in a non-invasive and accurate way. In this field, several processing tools are employed to extract the respiratory parameters from inertial data;therefore, an overview of algorithms and methods to determine the respiratory rate from acceleration data is provided. Finally, comparative analysis for all the covered topics are reported, providing useful insights to develop the next generation of wearable sensors for monitoring respiratory parameters.
ABSTRACT
Disposable surgical face masks are usually used by medical/nurse staff but the current Covid-19 pandemic has caused their massive use by many people. Being worn closely attached to the people's face, they are continuously subjected to routine movements, i.e., facial expressions, breathing, and talking. These motional forces represent an unusual source of wasted mechanical energy that can be rather harvested by electromechanical transducers and exploited to power mask-integrated sensors. Typically, piezoelectric and triboelectric nanogenerators are exploited to this aim; however, most of the current devices are too thick or wide, not really conformable, and affected by humidity, which make them hardly embeddable in a mask, in contact with skin. Different from recent attempts to fabricate smart energy-harvesting cloth masks, in this work, a wearable energy harvester is rather enclosed in the mask and can be reused and not disposed. The device is a metal-free hybrid piezoelectric nanogenerator (hPENG) based on soft biocompatible materials. In particular, poly(vinylidene fluoride) (PVDF) membranes in the pure form and with a biobased plasticizer (cardanol oil, CA) are electrospun onto a laser-ablated polyimide flexible substrate attached on a skin-conformable elastomeric blend of poly(dimethylsiloxane) (PDMS) and Ecoflex. The multilayer structure of the device harnesses the piezoelectricity of the PVDF nanofibers and the friction triboelectric effects. The ultrasensitive mechanoelectrical transduction properties of the composite device are determined by the strong electrostatic behavior of the membranes and the plasticization effect of cardanol. In addition, encapsulation based on PVDF, PDMS, CA, and parylene C is used, allowing the hPENG to exhibit optimal reliability and resistance against the wet and warm atmosphere around the face mask. The proposed device reveals potential applications for the future development of smart masks with coupled energy-harvesting devices, allowing to use them not only for anti-infective protection but also to supply sensors or active antibacterial/viral devices.