Perspiration Compensated Transdermal Alcohol Sensor for Personalized Medicine

Non-invasive continuous alcohol (ethanol) monitoring has potential applications in both population research and in clinical management of acute alcohol intoxication or chronic alcoholism. Current wearable monitors based on transdermal alcohol content (TAC) sensing have limited accessibility and blood alcohol content (BAC) quantification accuracy. In the first half of this work, we demonstrated a self-contained discreet wearable transdermal alcohol (TAC) sensor in the form of a wristband or armband. This sensor can detect vapor-phase alcohol in perspiration from 0.09 ppm (equivalent to 0.09 mg/dL sweat alcohol concentration at 25 °C under Henry’s Law equilibrium) to over 500 ppm at one-minute time resolution. Additionally, a digital sensor was employed to monitor the temperature and humidity levels inside the sensing chamber. Two male human subjects were recruited to conduct studies with alcohol consumption using calibrated prototype TAC sensors to validate the performance. Our preliminary data showed that, under well-controlled conditions, this sensor can acquire TAC curves at low doses (1-2 standard drinks). Moreover, TAC data for different doses can be easily distinguished. However, substantial interpersonal and intrapersonal variabilities in measurement data were also observed in experiments under less controlled conditions. Our observations suggest that perspiration rate might be an important contributing factor to these variabilities, which inspired us to develop a perspiration compensated TAC sensor. In the second half of this thesis, we carefully analyzed the mass transport process of ethanol and water vapors inside the sensing chamber to identify the root causes of sensor variabilities observed from our device. A mathematical model was developed to better understand the relationship between sensing current and ethanol concentration in liquid sweat. The resulted equation suggests that perspiration rate-induced sensor variabilities can potentially be compensated by two humidity measurements. Therefore, we updated the wearable TAC sensor design, integrating two additional digital temperature and humidity sensors. Internal components of the device were rearranged, reducing its overall size to 42 mm x 46 mm x 13 mm. Prototypes of the new TAC sensor were fabricated and characterized in our lab. Next, 10 repeated trials with alcohol administration (1 standard drink) were conducted by one subject to test the hypothesis on that individual. Normalized area under curve (AUC) and peak values were utilized to compare the sensor variabilities before and after compensation. Compared to TAC data without compensation, the variabilities of AUC and peak values were reduced by 45% and 64%, respectively. ANOVA f-tests were applied to test the hypothesis on this individual. The null hypothesis of the peak values has been rejected with an f statistic of 7.89 (p-value = 0.004). However, the test on AUC data yielded an f statistic of 3.35 (p-value = 0.054), indicating the null hypothesis of the AUC values was not rejected. Based on power analysis, 20 samples in total are required to draw a conclusion for AUC. Further studies with sufficient sample sizes are required to validate and characterize the impact of different perspiration rates on TAC sensors, which may inform more reproducible and accurate sensor designs in the future. In addition, the author also contributed to several other sensors and portable systems for personalized medicine and research. Two selected projects with major contributions were included in Chapter 9