Background: The complexity and variety of inhaled tobacco products have increased significantly with the introduction of Electronic Nicotine Delivery Systems (ENDS). Product characteristics and human behavior are the main factors affecting products' emissions, consumption, and health effects. Combining the understanding of these two factors informs the next generation of regulations of these products. Quantifying use patterns helps health care professionals provide informed treatment of users addicted to nicotine and tobacco products. The literature lacks comprehensive studies to characterize ENDS hardware and operation, such as heating element resistance, battery performance, power, and thermal management. Human behavior is measured as use topography, a temporal signal of the interaction between the user's mouth and the product. Traditional analysis of use topography focused on short-term puff dynamics, and overlooks extended session dynamics. The literature lacks the appropriate parameters and tools to quantify session dynamics over a long duration (i.e. days, weeks, months). Method and validation: This dissertation focuses on two aims: The first aim is to design methods to characterize the hardware and operation of modern ENDS devices and test their effects on ENDS performance. Parts of ENDS devices are repurposed to produce product-specific testing apparatus of effective coil resistance for several ENDS products. The effects of manufacturing variation in coil resistance on coil lifetime and Total Particulate Matter (TPM) are measured for one of the most popular pod-style ENDS. A method for dynamic measurement of electrical signals in modern ENDS is presented and validated for ENDS power management characterization. The second aim is to design and validate algorithms for quantifying chronic use topographies associated with inhaled tobacco products. The quantifying tool is designed based on autocorrelation to quantify chronic topography parameters including session period, and session duration as random distributions. These distributions provide insights into session topography dynamics over a day, a week, a month, and longer. Results: Significant variations in coil resistance were observed within and between brands such as the difference of 0.593 [Ω] (p < 0.001) between JUUL and Vuse ALTO. The mean resistance and standard deviation of the coil assemblies was shown to be μ= 1.031 (σ= 0.067) [Ω] for Vuse ALTO and μ= 1.624 (σ= 0.033)[Ω] for JUUL. The variation in coil resistance between products and within products can have significant impacts on aerosol emissions. Dynamic measurement of power in Vuse ALTO showed that voltage is delivered to the coil as pulses of ~119.5 Hz with duty cycles of 0.3 - 0.6 which found to be correlated with the energy and change in temperature in coil. The mass of the generated aerosol per puff was correlated with the energy per puff. Quantifying session topography method successfully worked with puff period, session period and session duration with mean absolute percentage error of 1.18 [%], 2.92 [%], 12.59 [%] respectively. The method showed resiliency to session dynamic variation with accepted percentage of 99.98 [%], 92.39 [%], and 76.21 [%] for puff period, session period and session duration respectively. The method appears sufficiently valid and robust for analysis of natural environment human subject behavioral studies of tobacco product use. Conclusions: The absence of e-liquid in the pod is an important factor in causing coil failure. Small bits of the degraded coil could be potentially introduced to the aerosol. Energy is an important, if not the most important, contributor to the yield generated form an ENDS. A method was demonstrated to dynamically measure coil temperature based on temperature coefficient of resistance (TCR). It was also shown that coil temperature can be controlled by the ENDS by changing the energy delivered to the coil per pulse which is intern controlled by duty cycle of the pulses using the PWM algorithm. The quantifying session topography method provides high value in investigating the effects of user environment such as a day of week on session dynamics. It also demonstrated an example of using the method for quantifying how product characteristics such as e-liquid flavors and nicotine concentration may moderate use behavior.

Publication Date


Document Type


Student Type


Degree Name

Electrical and Computer Engineering (Ph.D)

Department, Program, or Center

Electrical Engineering (KGCOE)


Edward Hensel

Advisor/Committee Member

Risa Robinson

Advisor/Committee Member

Andres Kwasinski


RIT – Main Campus

Plan Codes