From learning environments to battlefields to marketing teams, the desire to measure cognition and cognitive fatigue in real time has been a grand challenge in optimizing human performance. Near-infrared spectroscopy (NIRS) is an effective optical technique for measuring changes in subdermal hemodynamics, and it has been championed as a more practical method for monitoring brain function compared to MRI. This study reports on an innovative functional NIRS (fNIRS) sensor that integrates the entire system into a compact and wearable device, enabling long-term monitoring of patients. The device provides unrestricted mobility to the user with a Bluetooth connection for settings configuration and data transmission. A connected device, such as a smartphone or laptop equipped with the appropriate interface software, collects raw data, then stores and generates real-time analyses. Tests confirm the sensor is sensitive to oxy- and deoxy-hemoglobin changes on the forehead region, which indicate neuronal activity and provide information for brain activity monitoring studies.

Sleep staging has a very important role in diagnosing patients with sleep disorders. In general, this task is very time-consuming for physicians to perform. Deep learning shows great potential to automate this process and remove physician bias from decision making. In this study, we aim to identify recent trends on performance improvement and the causes for these trends. Recent papers on sleep stage classification and interpretability are investigated to explore different modeling and data manipulation techniques, their efficiency, and recent advances. We identify an improvement in performance up to 12% on standard datasets over the last 5 years. The improvements in performance do not appear to be necessarily correlated to the size of the models, but instead seem to be caused by incorporating new architectural components, such as the use of transformers and contrastive learning.

The use of benign stimuli to control the binding and release of labile biologics for their isolation from complex feedstocks is a key goal of modern biopharmaceutical technology. This study introduces cyclic azobenzene‐peptide (CAP) ligands for the rapid and discrete photo‐responsive capture and release of blood coagulation factor VIII (FVIII). A predictive method—based on amino acid sequence and molecular architecture of CAPs—is developed to correlate the conformation of cis/trans‐CAP photo‐isomers to FVIII binding and release. Combined in silico ‐ in vitro analysis of FVIII:peptide interactions guide the design of a rational approach to optimize isomerization kinetics and biorecognition of CAPs. A photoaffinity adsorbent, prepared by conjugating selected CAP G‐cyclo_AZOB[Lys‐YYKHLYN‐Lys]‐G on translucent chromatographic beads, features high binding capacity (>6 mg of FVIII per mL of resin) and rapid photo‐isomerization kinetics (τ < 30 s) when exposed to 420–450 nm light at the intensity of 0.1 W cm⁻². The adsorbent purifies FVIII from a recombinant harvest using a single mobile phase, affording high product yield (>90%), purity (>95%), and blood clotting activity. The CAPs introduced in this report demonstrate a novel route integrating gentle operational conditions in a rapid and efficient bioprocess for the purification of life‐saving biotherapeutics.

In this paper, SkinAid , a battery-free, low-cost, robust, and user-friendly smart bandage for electrochemical monitoring and sensing of chronic wounds is proposed. The working principle of the bandage is based on direct frequency modulation of a tri-electrode electrochemical sensing of wound data. The electronics and biotelemetry links were realized using low-cost manufacturing process of textile embroidery onto fabric substrate. The transmitter was represented by a bedsheet with novel corrugated crossed-dipole made of Elektrisola-7 embroidered onto gauze fabric. An input RF signal of 1 W was transmitted at 462 MHz from the bedsheet to the all-textile bandage featuring a rectifying circuit, a voltage-controlled oscillator (VCO), an electrochemical sensor, and a 915-MHz dipole for re-transmission of the modulated wound data. We demonstrate that for wound fluid emulated by various uric acid concentrations from 0.2 mM to 1.2 mM, corresponding modulated frequency varies from 1090 MHz to 1145 MHz for signals captured at 25 cm away from the bandage. For pH modulation ranging from 2 to 10, the corresponding modulated frequency was between 800 MHz and 830 MHz for signals received at more than 6 feet away from the bandage. For quick and reliable assessment, two empirical models were developed for the direct frequency modulation as a function of uric acid and pH. To the best of our knowledge, this is the first time an all-textile (fabric-integrated), battery-free and wirelessly powered smart bandage have been proposed for wound monitoring. This result can be used as a first step in developing RFID-type, battery-free, and low-cost 5 G/6 G smart bandages using millimeterwave and terahertz frequencies where the bedsheet can be host to a MIMO-aided beamforming.

Humans have searched far beyond our planet to understand the fundamental principles and mechanisms of life