Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina, myocardial infarction, and ischemic heart failure, are the leading cause of death globally. Early detection and treatment of CVDs significantly contribute to the prevention or delay of cardiovascular death. Electrocardiogram (ECG) records the electrical impulses generated by heart muscles, which reflect regular or irregular beating activity. Computer-aided techniques provide fast and accurate tools to identify CVDs using a patient’s ECG signal, which have achieved great success in recent years. Latest computational diagnostic techniques based on ECG signals for estimating CVDs conditions are summarized here. The procedure of ECG signals analysis is discussed in several subsections, including data preprocessing, feature engineering, classification, and application. In particular, the End-to-End models integrate feature extraction and classification into learning algorithms, which not only greatly simplifies the process of data analysis, but also shows excellent accuracy and robustness. Portable devices enable users to monitor their cardiovascular status at any time, bringing new scenarios as well as challenges to the application of ECG algorithms. Computational diagnostic techniques for ECG signal analysis show great potential for helping health care professionals, and their application in daily life benefits both patients and sub-healthy people.

Surface-enhanced Raman scattering (SERS) as a powerful non-invasive spectroscopic technique has been intensively used in bio/chemical sensing, enabling ultrasensitive detection of various analytes and high specificity with a fingerprint-like characteristic. Flexible SERS sensors conformally adapting to nonplanar surfaces and allowing swab-sampling or in-situ detection of analytes, which are not achievable for rigid SERS sensors, greatly meet the demand of onsite and real-time diagnostics. However, the rational design and fabrication of flexible SERS-based sensors for point-of-care diagnostics aiming to simultaneously achieve extremely high sensitivity, stability, and good signal reproducibility remain many challenges. We present a state-of-the-art review of the flexible SERS sensors. Attentions are devoted to engineering plasmonic substrates for improving the performance of flexible SERS devices. Strategies of constructing the flexible SERS sensors toward point-of-care detection are investigated in depth. Advanced algorithms assisting the SERS data process are also presented for intelligently distinguishing the species and contents of analytes. The promising applications of flexible SERS sensors in medical diagnostics, environmental analyses, food safety, and forensic science are displayed. The flexible SERS devices serving as powerful analytical tools shed new light on the in-situ and point-of-care detection of real-world analytes in a convenient, facile, and nondestructive manner, and especially are conceivable to serve as next-generation wearable sensors for healthcare.

A systematic summary from mechanisms, sensors based on nanomaterials and nanostructures, algorithms, to multifunctional devices for smart healthcare.

Microneedle (MN) technology is a rising star in the point-of-care (POC) field, which has gained increasing attention from scientists and clinics. MN-based POC devices show great potential for detecting various analytes of clinical interests and transdermal drug delivery in a minimally invasive manner owing to MNs’ micro-size sharp tips and ease of use. This review aims to go through the recent achievements in MN-based devices by investigating the selection of materials, fabrication techniques, classification, and application, respectively. We further highlight critical aspects of MN platforms for transdermal biofluids extraction, diagnosis, and drug delivery assisted disease therapy. Moreover, multifunctional MNs for stimulus-responsive drug delivery systems were discussed, which show incredible potential for accurate and efficient disease treatment in dynamic environments for a long period of time. In addition, we also discuss the remaining challenges and emerging trend of MN-based POC devices from the bench to the bedside.

The development of sensors with high sensitivity, good flexibility, low cost, and capability of detecting multiple inputs is of great significance for wearable electronics. Herein, we report a napkin-based wearable capacitive sensor fabricated by a novel, low-cost, and facile strategy. The capacitive sensor is composed of two pieces of electrode plates manufactured by spontaneous assembly of silver nanowires (NWs) on a polydimethylsiloxane (PDMS)-patterned napkin. The sensor possesses high sensitivity (>7.492 kPa⁻¹), low cost, and capability for simultaneous detection of multiple signals. We demonstrate that the capacitive sensor can be applied to identify a variety of human physiological signals, including finger motions, eye blinking, and minute wrist pulse. More interestingly, the capacitive sensor comfortably attached to the temple can simultaneously monitor eye blinking and blood pulse. The demonstrated sensor shows great prospects in the applications of human–machine interface, prosthetics, home-based healthcare, and flexible touch panels.