Abstract—The implementation of the emotion reasoning systems to these days has been on software level; the software evaluates emotional states based on the amount of changes in biological signals. Therefore, the memory consumption and computational overload would increase with the number of parameters used, and the overall effect would be an increased the response time needed to acquire the needed emotion reasoning results. In this paper, we go over the design of a One-Chip hardware reasoning block dedicated to emotion based applications that are capable of processing multiple, real-time information, and the design an emotion reasoning system utilizing this chip. Our system provides an emotion reasoning API for the interaction between sensing and reasoning blocks so that the hardware emotion reasoning device can be easily utilized by emotion based service applications. In addition, it is possible to manufacture accessory devices for smartphones based on downsized reasoning block hardware with USB and Bluetooth interface for use with emotion based mobile services. Index Terms—Emotion reasoning, emotion inference. I. INTRODUCTION In order to acquire numerical values that can be used to infer about individuals’ emotional states, sensors that measure variables such as PPG (Photoplethysmogram), GSR(Galvanic Skin Response), and SKT(Skin Temperature) are used [1], [2]. However, individuals’ actual emotional states are likely to differ even under identical conditions [3], [4], and environmental factors such as temperature and humidity affect individuals’ emotions differently. Therefore, not only the biological data gathered from the mentioned sensors but also additional factors that could influence individuals’ emotions should be considered. Diverse types of data along with the feedback from users’ unique emotional states can help obtain a more truthful picture of human emotional states. An emotion reasoning system can be divided largely two parts, a sensing block and a reasoning block. The sensing block utilizes a few sensors to send biological signals acquired from sensors for PPG, GSR, SKT, HR (heart rate), etc. from the human body to the reasoning block. Depending on whether the sensor output values have increased, decreased, or remained the same, the reasoning block then makes an evaluation of the current emotional state based on a Manuscript received January 25, 2013; revised March 25, 2013. This work was supported by the IT R&D program of MKE/KEIT. [2009-S-014-01, On the development of Sensing based Emotive Service Mobile Handheld Devices] The authors are with the Wireless Convergence Platform Research Center, Korea Electronics Technology Institute, Seoul, Korea (e-mail: busytom@ keti.re.kr, solim@keti.re.kr, ycpark@keti.re.kr, bhpark34@keti.re.kr, tipsiness@gmail.com). rule-base table. Hence, the number of entries in the rule-base table in the reasoning block increases with the number of parameters needed for making decision, and this degrades the computational speed. In this paper, we discuss the design and implementation for an emotion reasoning system based on One-Chip integral emotion reasoning hardware. By constructing the reasoning block on a single hardware device, one can achieve lower memory consumption and faster computational speed. Since the one-chip emotion reasoning hardware can be refined for use in smartphones and smartpads as an accessory device, this design can form the basis for diversification of emotion based contents. II. EMOTION REASONING In emotion reasoning systems, the sensing block collects biological data and transmits to the reasoning block. In software-based systems, the reasoning block receives the data collected in the sensing block, processes it as necessary, and defines the current emotional state as one of the following: pleasant, unpleasant, aroused, relaxed, pleasantly aroused, pleasantly-relaxed, unpleasantly aroused, unpleasantly-relaxed, or neutral. Additionally, parameters such as environmental temperature that could affect emotional states can be used to further define emotional Fig. 1. Emotion reasoning results. Fig. 2. Basic rule-base table. For emotion reasoning, a rule-based table [6], [7] pertaining to sensed data value decrease or increase is used. Say there are four parameters being used, namely PPG, GSR, A Design and Implementation of an Emotion Reasoning Chip Based Emotion Reasoning System Yong-Seok Lim, Seung-Ok Lim, Young-Choong Park, Byoung-Ha Park, and Joongjin Kook 131 DOI: 10.7763/LNSE.2013.V1.29 states [5]. The final resulting evaluation is shown in Fig. 1. Lecture Notes on Software Engineering, Vol. 1, No. 2, May 2013