Classification of Sleep-Wake State in Ballistocardiogram system based on Deep Learning.

Sleep state classification is essential for managing and comprehending sleep patterns, and it is usually the first step in identifying sleep disorders. Polysomnography (PSG), the gold standard, is intrusive and inconvenient for regular/long-term sleep monitoring. Many sleep-monitoring techniques have recently seen a resurgence as a result of the rise of neural networks and advanced computing. Ballistocardiography (BCG) is an example of such a technique, in which vitals are monitored in a contactless and unobtrusive manner by measuring the body's reaction to cardiac ejection forces. A Multi-Headed Deep Neural Network is proposed in this study to accurately classify sleep-wake state and predict sleep-wake time using BCG sensors. This method achieves a 95.5% sleep-wake classification score. Two studies were conducted in a controlled and uncontrolled environment to assess the accuracy of sleep-awake time prediction. Sleep-awake time prediction achieved an accuracy score of 94.16% in a controlled environment on 115 subjects and 94.90% in an uncontrolled environment on 350 subjects. The high accuracy and contactless nature make this proposed system a convenient method for long-term monitoring of sleep states, and it may also aid in identifying sleep stages and other sleep-related disorders. Clinical Relevance- Current sleep-wake state classification methods, such as actigraphy and polysomnography, necessitate patient contact and a high level of patient compliance. The proposed BCG method was found to be comparable to the gold standard PSG and most wearable actigraphy techniques, and also represents an effective method of contactless sleep monitoring. As a result, clinicians can use it to easily screen for sleep disorders such as dyssomnia and sleep apnea, even from the comfort of one's own home.

Validation of Dozee, a Ballistocardiography-based Device, for Contactless and Continuous Heart Rate and Respiratory Rate Measurement.

Long-term acquisition of respiratory and heart signals is useful in a variety of applications, including sleep analysis, monitoring of respiratory and heart disorders, and so on. Ballistocardiography (BCG), a non-invasive technique that measures micro-body vibrations caused by cardiac contractions as well as motion caused by breathing, snoring, and body movements, would be ideal for long-term vital parameter acquisition. Turtle Shell Technologies Pvt. Ltd.'s Dozee device, which is based on BCG, is a contactless continuous vital parameters monitoring system. It is designed to measure Heart Rate (HR) and Respiratory Rate (RR) continuously and without contact in a hospital setting or at home. A validation study for HR and RR was conducted using Dozee by comparing it to the vitals obtained from the FDA-approved Patient Monitor. This was done in a sleep laboratory setting over 110 nights in 51 subjects to evaluate HR and over 20 nights in 17 subjects to evaluate RR at the National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India. Approximately 789 hours data for HR and approximately 112 hours data for RR was collected. Dozee was able to achieve a mean absolute error of 1.72 bpm for HR compared to the gold standard ECG. A mean absolute error of ∼1.24 breaths/min was obtained in determining RR compared to currently used methods. Dozee is ideal for long-term contactless monitoring of vital parameters due to its low mean absolute errors in measuring both HR and RR. Clinical Relevance- Continuous and long-term vitals monitoring is known to enable early screening of clinical deterioration, improve patient outcomes and reduce mortality. Current methods of continuous monitoring are overly complex, costly, and rely heavily on patient compliance. The proposed remote vitals monitoring solution based on BCG was found to be at par with gold standard methods of recording HR and RR. As a result, clinicians can use it to effectively monitor patients in both the hospital and at home.

Effect of Tamarind Gum on the Properties of Phase-Separated Poly(vinyl alcohol) Films.

The current study aims to evaluate the effect of tamarind gum (TG) on the optical, mechanical, and drug release potential of poly(vinyl alcohol) (PVA)-based films. This involves preparing PVA-TG composite films with different concentrations of TG through a simple solvent casting method. The addition of TG has enhanced the phase separation and aggregation of PVA within the films, and it becomes greater with the increase in TG concentration. Brightfield and polarized light micrographs have revealed that aggregation is favored by forming crystalline domains at the PVA-TG interface. The interconnected network of PVA-TG aggregates influenced the swelling and drying properties of the films. Using Peleg's analysis, the mechanical behavior of films was determined by their stress relaxation profiles. The addition of TG has made no significant changes to the firmness and viscoelastic properties of films. However, long-durational relaxation times indicated that the interconnected network might break down in films with higher TG concentration, suggesting their brittleness. The controlled release of ciprofloxacin in HCl solution (0.5% (w/v)) appears to decrease with the increase in TG concentration. In fact, TG has inversely affected the impedance and altered the ionic conductivity within the films. This seems to have directly influenced the drug release from the films as the mechanism was found to be non-Fickian diffusion (based on Korsmeyer-Peepas and Peppas-Sahlin kinetic models). The antimicrobial study using Escherichia coli was carried out to evaluate the activity of the drug-loaded films. The study proves that TG can modulate the properties of PVA films and has the potential to fine-tune the controlled release of drugs from composite films.

Synthesis and characterization of novel tamarind gum and rice bran oil-based emulgels for the ocular delivery of antibiotics.

In this study, we developed tamarind gum (TG) and rice bran oil (RBO)-based emulgels. The control formulation (TR0), did not contain RBO. The emulgels were named as TR1, TR2, TR3, and TR4, which contained 5% (w/w), 10% (w/w), 15% (w/w), and 20% (w/w/) of RBO, respectively. The microscopic studies showed that the emulgels were biphasic in nature. FTIR spectroscopy revealed the reduction in the hydrogen bonding with an increase in the RBO content. Impedance profiles suggested that the resistive component of the emulgels was increased as the RBO content was increased. The thermal analysis suggested that the addition of RBO reduced the water holding capacity of the emulgels. Stress relaxation studies revealed that the fluidic component was considerably higher in TG/RBO-based emulgels as compared to TR0. In vitro release study of the model drug (ciprofloxacin HCl; a hydrochloride salt of ciprofloxacin) suggested a significantly lower release from the emulgel matrices (TR1-TR4) in comparison to TR0. However, ex vivo corneal permeation of the drug increased with an increase in the RBO content. Since the emulgels were able to improve the corneal permeation of the model drug, the emulgels can be explored to deliver drugs to the internal structures of the eye.