Haptic Identification of Stiffness and Force Magnitude Steven A. Cholewiak, 1 Hong Z. Tan, 1 and David S. Ebert 2,3 1 Haptic Interface Research Laboratory 2 Purdue University Rendering and Perceptualization Lab 3 Purdue University Regional Visualization & Analytics Center Purdue University, West Lafayette, Indiana, USA ABSTRACT As haptics becomes an integral component of scientific data visualization systems, there is a growing need to study “haptic glyphs” (building blocks for displaying information through the sense of touch) and quantify their information transmission capability. The present study investigated the channel capacity for transmitting information through stiffness or force magnitude. Specifically, we measured the number of stiffness or force- magnitude levels that can be reliably identified in an absolute identification paradigm. The range of stiffness and force magnitude used in the present study, 0.2-3.0 N/mm and 0.1-5.0 N, respectively, was typical of the parameter values encountered in most virtual reality or data visualization applications. Ten individuals participated in a stiffness identification experiment, each completing 250 trials. Subsequently, four of these individuals and six additional participants completed 250 trials in a force-magnitude identification experiment. A custom-designed 3 degrees-of-freedom force-feedback device, the ministick, was used for stimulus delivery. The results showed an average information transfer of 1.46 bits for stiffness identification, or equivalently, 2.8 correctly-identifiable stiffness levels. The average information transfer for force magnitude was 1.54 bits, or equivalently, 2.9 correctly-identifiable force magnitudes. Therefore, on average, the participants could only reliably identify 2-3 stiffness levels in the range of 0.2-3.0 N/mm, and 2-3 force- magnitude levels in the range of 0.1-5.0 N. Individual performance varied from 1 to 4 correctly-identifiable stiffness levels and 2 to 4 correctly-identifiable force-magnitude levels. Our results are consistent with reported information transfers for haptic stimuli. Based on the present study, it is recommended that 2 stiffness or force-magnitude levels (i.e., high and low) be used with haptic glyphs in a data visualization system, with an additional third level (medium) for more experienced users. KEYWORDS: Identification, information transfer, haptic perception, stiffness, force, force magnitude, data visualization, perceptualization. INDEX TERMS: C.0 [Computer Systems Organization]: General - Hardware/software interfaces; J.4 [Computer Applications]: Social and Behavioral Sciences - Psychology 1 INTRODUCTION The present study was motivated by the need for a better understanding of the use of “haptic glyphs” in a scientific data perceptualization system. The term haptic glyph refers to the basic unit for displaying information through the sense of touch. The term perceptualization is used to emphasize the use of haptic and auditory displays in a data visualization system. The goal of any perceptualization system is to convey a large amount of information to users in an efficient and intuitive manner with a minimum cognitive load. The last decade has witnessed rapid advancements in incorporating haptic feedback into data visualization systems (e.g., [1-7]). Although there exist many guidelines on how information should be displayed visually (e.g., [8, 9]), the design of “haptic glyphs” is still in its infancy (although see [10] for the design of “haptic icons”; and [11] for a study of “tactons” – tactile icons). A variable in a data perceptualization system can be either continuous or discrete. To represent a continuous variable with a haptic signal, a knowledge of the Weber fraction – the percentage change in the signal that can be barely noticed – is useful. Past studies of haptic signals using a discrimination paradigm have established a Weber fraction of 3-10% for length by the finger- span method [12], 5-10% for force magnitude [13-15], 13% for torque [16, 17], 22% for stiffness [18-20] and 34% for viscosity [21]. The discrimination thresholds for some other haptic signals did not increase with the reference signal as predicted by Weber’s Law. They instead remained constant; e.g., the discrimination threshold was 2.0-2.7° for joint-angle position [22] and 25-35° for force direction [23, 24]. To represent a discrete variable with a haptic signal, a knowledge of channel capacity – the maximum amount of information that can be transmitted through the signal – is required. From the information transfer measurement, we can estimate the number of signal levels that can be correctly identified, which translates into the number of categories a particular haptic signal can represent without confusion. In general, our ability to identify the value of a parameter in isolation is limited [25]. Past absolute identification studies have reported an information transfer of 2 bits (4 correctly-identifiable items) for length by the finger-span method [12], 1.7-1.9 bits (3-4 items) for joint-angle position [22] and 3-4 items for size [26, 27]. One recent study of tactons on mobile devices demonstrated that users could reliably identify 2-3 types of rhythms, 1 type of roughness and 2-3 locations of vibrotactile stimuli on the forearm when the three vibrotactile signal attributes were presented simultaneously [11]. To the best of our knowledge, no data exist on the human ability to identify surface stiffness or force magnitude. Therefore, the goal of the present study was to establish the information- transmission capabilities of stiffness and force-magnitude through the haptic channel. The rest of this article is organized as follows. Section 2 describes the methods common to the stiffness and force-magnitude identification experiments. Sections 3 and 4 present more details and the results of the two experiments, respectively. Section 5 concludes the article. Email: scholewi@eden.rutgers.edu; hongtan@purdue.edu, ebertd@purdue.edu. 87 Symposium on Haptic Interfaces for Virtual Environments and Teleoperator Systems 2008 13-14 March, Reno, Nevada, USA 978-1-4244-2005-6/08/$25.00 ©2008 IEEE