Wearable alcohol monitoring devices demand noninvasive, real-time measurement of blood alcohol content (BAC) reliably and continuously. A few commercial devices are available to determine BAC noninvasively by detecting transcutaneous diffused alcohol. However, they suffer from a lack of accuracy and reliability in the determination of BAC in real time due to the complex scenario of the human skin for transcutaneous alcohol diffusion and numerous factors (e.g., skin thickness, kinetics of alcohol, body weight, age, sex, metabolism rate, etc.). In this work, a transcutaneous alcohol diffusion model has been developed from real-time captured data from human wrists to better understand the kinetics of diffused alcohol from blood to different skin epidermis layers. Such a model will be a footprint to determine a base computational model in larger studies. Eight anonymous volunteers participated in this pilot study. A laboratory-built wearable blood alcohol content (BAC) monitoring device collected all the data to develop this diffusion model. The proton exchange membrane fuel cell (PEMFC) sensor was fabricated and integrated with an nRF51822 microcontroller, LMP91000 miniaturized potentiostat, 2.4 GHz transceiver supporting Bluetooth low energy (BLE), and all the necessary electronic components to build this wearable BAC monitoring device. The %BAC data in real time were collected using this device from these volunteers’ wrists and stored in the end device (e.g., smartphone). From the captured data, we demonstrate how the volatile alcohol concentration on the skin varies over time by comparing the alcohol concentration in the initial stage (= 10 min) and later time (= 100 min). We also compare the experimental results with the outputs of three different input profiles: piecewise linear, exponential linear, and Hoerl, to optimize the developed diffusion model. Our results demonstrate that the exponential linear function best fits the experimental data compared to the piecewise linear and Hoerl functions. Moreover, we have studied the impact of skin epidermis thickness within ±20% and demonstrate that a 20% decrease in this thickness results in faster dynamics compared to thicker skin. The model clearly shows how the diffusion front changes within a skin epidermis layer with time. We further verified that 60 min was roughly the time to reach the maximum concentration, C_max, in the stratum corneum from the transient analysis. Lastly, we found that a more significant time difference between BAC_max and C_max was due to greater alcohol consumption for a fixed absorption time.

Peristalsis, the coordinated contraction and relaxation of the muscles of the stomach, is important for normal gastric motility and is impaired in motility disorders. Coordinated electrical depolarizations that originate and propagate within a mutually coupled network of interstitial cells of Cajal (ICC) and smooth muscle cells of the stomach wall as a slow-wave, underly peristalsis. Normally, the gastric slow-wave (GSW) oscillates with a single period and uniform rostro-caudal lag, exhibiting network entrainment. Loss of entrainment in the coupled network and the resulting impairment in slow-wave propagation is associated with various gastric motility disorders. Our study provides an enhanced understanding of physiological mechanisms that may underlie gastric motility disorders. This understanding may benefit in the design of new drugs and treatment therapies targeted to specific cellular pathways as well as improvements in current therapies such as gastric pacemaking neurotechnology. We hypothesize that engaging biological oscillators (ICCs) through second messenger pathways permits robust entrainment essential for gastric peristalsis, which can be disrupted by gap junction deficiency or elevated neurotransmitter release. Using a computational framework, we show that stronger electrical coupling and exchange of second messengers (in particular, inositol trisphosphate (IP3)) are complementary mechanisms and increase the range of the entrained network. We also show that the distinct intercellular coupling in conjunction with the intracellular feedback pathways and a rostro-caudal neural stimulus gradient allows the gastric slow-wave to oscillate within a moderate range of frequencies and to propagate with a broad range of velocities, thus preventing decoupling observed in motility disorders. We find that aberrant responses of different parts of the stomach (corpus, antrum etc.) to exogenous application of excitatory neurotransmitters such as Acetylcholine, can be explained by an interplay between the level of neurotransmitter and density of receptors available while blockade of gap junctions (which mimics gap junction deficiency) results in retrograde propagation of the slow-wave. To address our hypotheses, a physiologically based computational framework was used to develop a novel gastric motility network model. Along with the widely assumed electrical gap junction coupling between the ICCs, we incorporated constitutive movement of second messengers, namely IP3 and Ca2+ between ICC. We also included a rostro-caudal linear decreasing gradient of neural stimulus to the ICC along the length of the stomach to mimic enteric neurotransmitter release and a reverse increasing gradient of muscarinic receptor density. Overall, this study provides us novel mechanistic understanding of the neurotransmitter release and its downstream action on emergent