Ahyoung Choi

Physiological evidence for a dual process model of the social effects of emotion in computers

There has been recent interest on the impact of emotional expressions of computers on peoples decision making. However, despite a growing body of empirical work, the mechanism underlying such effects is still not clearly understood. To address this issue the paper explores two kinds of processes studied by emotion theorists in human-human interaction: inferential processes, whereby people retrieve information from emotion expressions about others beliefs, desires, and intentions; affective processes, whereby emotion expressions evoke emotions in others, which then influence their decisions. To tease apart these two processes as they occur in human-computer interaction, we looked at physiological measures (electrodermal activity and heart rate deceleration). We present two experiments where participants engaged in social dilemmas with embodied agents that expressed emotion. Our results show, first, that peoples decisions were influenced by affective and cognitive processes and, according to the prevailing process, people behaved differently and formed contrasting subjective ratings of the agents; second we show that an individual trait known as electrodermal lability, which measures peoples physiological sensitivity, predicted the extent to which affective or inferential processes dominated the interaction. We discuss implications for the design of embodied agents and decision making systems that use emotion expression to enhance interaction between humans and computers. We show that computers emotional displays have a deep impact on peoples decision making.We show that these effects of emotion displays occur through affective and cognitive processes.These processes can lead to distinct decision behavior and subjective impressions.Electrodermal lability, an individual trait, predicts which process dominates the interaction.

Smartphone-Based Bioelectrical Impedance Analysis Devices for Daily Obesity Management

Current bioelectric impedance analysis (BIA) systems are often large, cumbersome devices which require strict electrode placement on the user, thus inhibiting mobile capabilities. In this work, we developed a handheld BIA device that measures impedance from multiple frequencies (5 kHz~200 kHz) with four contact electrodes and evaluated the BIA device against standard body composition analysis systems: a dual-energy X-ray absorptiometry (DXA) system (GE Lunar Prodigy, GE Healthcare, Buckinghamshire, UK) and a whole-body BIA system (InBody S10, InBody, Co. Ltd, Seoul, Korea). In the study, 568 healthy participants, varying widely in body mass index, age, and gender, were recruited at two research centers: the Samsung Medical Center (SMC) in South Korea and the Pennington Biomedical Research Center (PBRC) in the United States. From the measured impedance data, we analyzed individual body fat and skeletal muscle mass by applying linear regression analysis against target reference data. Results indicated strong correlations of impedance measurements between the prototype pathways and corresponding InBody S10 electrical pathways (R = 0.93, p < 0.0001). Additionally, body fat estimates from DXA did not yield significant differences (p > 0.728 (paired t-test), DXA mean body fat 29.45 ± 10.77 kg, estimated body fat 29.52 ± 12.53 kg). Thus, this portable BIA system shows a promising ability to estimate an individual’s body composition that is comparable to large stationary BIA systems.

Mobile evaluation of human energy balance and weight control: Potential for future developments.

Quantification of energy storage is essential in understanding energy balance and can be determined by bioelectrical impedance analysis (BIA). Here, we have developed a smartphone form factor multi-frequency BIA device that incorporates an analog front end for body composition measurements. The device was compared against a reference gel-electrode based BIA system in a clinical trial of 311 subjects for predicting BIA equations by calibrating the impedance index to body composition data from dual energy X-ray absorptiometry (DXA). Strong correlations were observed between DXA-based lean soft tissue and the impedance index generated at 50 KHz (R2=0.87; p<;0.001). A similar trend was also evident at higher frequencies which matched results from the reference gel-electrode BIA device. The findings support the role of our consumer-oriented mobile Health initiative for multi-frequency BIA assessments to aid weight management.

Mind Your Composition: Clinical validation of Samsung's pocket-based bioelectrical impedance analyzers may increase consumer interest in personal health management.

Technological advances and clinical validation have enabled the use of BIA for body-composition monitoring for over 30 years. However, the rise of digital and mobile health innovations allows Samsung to integrate BIA as an additional physiological sensing modality in small-form-factor mobile devices for seamless lifestyle incorporation and to achieve more user-centric health management. The BIA clinical trials are helping to validate the devices along with the body-composition-prediction equations and algorithms to increase awareness among both consumers and their health care providers.