Wearable wireless skin conductance sensor and housing

Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2005.Includes bibliographical references (p. 48-49).This thesis report details the design and manufacture of HandWave, a wearable wireless Bluetooth skin conductance sensor, and dedicated housing. The HandWave collects Electrodermal Activity (EDA) data by measuring skin conductance over a pair of electrodes. The EDA data signal is used to infer the excitement level of the subject. The injection-molded housing is affixed to the wrist of the subject, and the electrodes are positioned on the fingers and/or palm. The HandWave amplification board utilizes a PIC to sample the EDA signal level with an analog-to-digital converter (ADC), control the gain of the amplification circuitry, and pass the data to a Bluetooth module. The Bluetooth module manages the wireless connection to a remote base-station and streams the EDA data over this link. Driver software on the base-station recomposes the EDA signal into standard units of conductance for display or further analysis.by Marc D. Strauss.S.B

Design and evaluation of iCalm : a novel, wrist-worn, low-power, low-cost, wireless physiological sensor module

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 151-156).The impracticality of the ambulatory electrocardiogram for long-term physiological monitoring has lead to the development of many new, compact sensors that have been designed with form factor and user comfort in mind. Nevertheless, there currently is no single sensor module that would be ideal to use for continuous, long-term monitoring. The sensors tend to either lack wireless capabilities, have a short battery life, or are financially unfeasible. After conducting a quick survey of recently developed sensors, we propose the design of iCalm: a novel, wrist-worn, low-power, low-cost, and wireless physiological sensor module. Its performance is compared against an FDA-approved platform through numerous experiments, including a few user studies. The iCalm skin conductance sensor greatly reduced noise due to motion and pressure artifacts; the iCalm heart rate sensor performed similar to the FDA-approved sensor. In addition, all of the participants in the experiments preferred the iCalm to the FDA-approved comparison sensors we tested. With iCalm, we hope to enable comfortable, long-term monitoring of the autonomic nervous system physiology and improve upon the current commercial sensors on the market.by Hoda Eydgahi.S.M

Adversarial uses of affective computing and ethical implications

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2005.Page 158 blank.Includes bibliographical references (p. 141-145).Much existing affective computing research focuses on systems designed to use information related to emotion to benefit users. Many technologies are used in situations their designers didn't anticipate and would not have intended. This thesis discusses several adversarial uses of affective computing: use of systems with the goal of hindering some users. The approach taken is twofold: first experimental observation of use of systems that collect affective signals and transmit them to an adversary; second discussion of normative ethical judgments regarding adversarial uses of these same systems. This thesis examines three adversarial contexts: the Quiz Experiment, the Interview Experiment, and the Poker Experiment. In the quiz experiment, participants perform a tedious task that allows increasing their monetary reward by reporting they solved more problems than they actually did. The Interview Experiment centers on a job interview where some participants hide or distort information, interviewers are rewarded for hiring the honest, and where interviewees are rewarded for being hired. In the Poker Experiment subjects are asked to play a simple poker-like game against an adversary who has extra affective or game state information.(cont.) These experiments extend existing work on ethical implications of polygraphs by considering variables (e.g. context or power relationships) other than recognition rate and using systems where information is completely mediated by computers. In all three experiments it is hypothesized that participants using systems that sense and transmit affective information to an adversary will have degraded performance and significantly different ethical evaluations than those using comparable systems that do not sense or transmit affective information. Analysis of the results of these experiments shows a complex situation in which the context of using affective computing systems bears heavily on reports dealing with ethical implications. The contribution of this thesis is these novel experiments that solicit participant opinion about ethical implications of actual affective computing systems and dimensional metaethics, a procedure for anticipating ethical problems with affective computing systems.by Carson Jonathan Reynolds.Ph.D

Motion and emotion estimation for robotic autism intervention.

Robots have recently emerged as a novel approach to treating autism spectrum disorder (ASD). A robot can be programmed to interact with children with ASD in order to reinforce positive social skills in a non-threatening environment. In prior work, robots were employed in interaction sessions with ASD children, but their sensory and learning abilities were limited, while a human therapist was heavily involved in “puppeteering” the robot. The objective of this work is to create the next-generation autism robot that includes several new interactive and decision-making capabilities that are not found in prior technology. Two of the main features that this robot would need to have is the ability to quantitatively estimate the patient’s motion performance and to correctly classify their emotions. This would allow for the potential diagnosis of autism and the ability to help autistic patients practice their skills. Therefore, in this thesis, we engineered components for a human-robot interaction system and confirmed them in experiments with the robots Baxter and Zeno, the sensors Empatica E4 and Kinect, and, finally, the open-source pose estimation software OpenPose. The Empatica E4 wristband is a wearable device that collects physiological measurements in real time from a test subject. Measurements were collected from ASD patients during human-robot interaction activities. Using this data and labels of attentiveness from a trained coder, a classifier was developed that provides a prediction of the patient’s level of engagement. The classifier outputs this prediction to a robot or supervising adult, allowing for decisions during intervention activities to keep the attention of the patient with autism. The CMU Perceptual Computing Lab’s OpenPose software package enables body, face, and hand tracking using an RGB camera (e.g., web camera) or an RGB-D camera (e.g., Microsoft Kinect). Integrating OpenPose with a robot allows the robot to collect information on user motion intent and perform motion imitation. In this work, we developed such a teleoperation interface with the Baxter robot. Finally, a novel algorithm, called Segment-based Online Dynamic Time Warping (SoDTW), and metric are proposed to help in the diagnosis of ASD. Social Robot Zeno, a childlike robot developed by Hanson Robotics, was used to test this algorithm and metric. Using the proposed algorithm, it is possible to classify a subject’s motion into different speeds or to use the resulting SoDTW score to evaluate the subject’s abilities

Ontologies for Intelligent e-Theraoy: Application to Obesity

[EN] In this paper we propose a new approach for mental e-health treatments named intelligent e-therapy (e-it) with capabilities for ambient intelligence and ubiquitous computing. The proposed e-it system supposes an evolution of cybertherapy and telepsychology tools used up to now. The e-it system is based in a knowledge base that includes all the knowledge related to the disorder and its treatment. We introduce the use of ontologies as the best option for the design of this knowledge base. We also present a fist e-it system for obesity treatment called etiobeZaragozá Álvarez, I.; Guixeres Provinciale, J.; Alcañiz Raya, ML. (2009). Ontologies for Intelligent e-Theraoy: Application to Obesity. Lecture Notes in Computer Science. 5518:894-901. doi:10.1007/978-3-642-02481-8_136S8949015518Baños, R.M., Botella, C., Perpiñá, C., Alcañiz, M., Lozano, J.A., Osma, J., Gallardo, M.: Virtual reality treatment of flying phobia. IEEE Transactions on Information Technology in Biomedicine 6(3), 206–212 (2002)Botella, C., Baños, R.M., Perpiña, C., et al.: Virtual reality treatment of claustrophobia: a case report. Behaviour Research & Therapy 36, 239–246 (1998)Hu, B., Dasmahapatra, S., Dupplaw, D., Lewis, P., Shadbolt, N.: Reflections on a medical ontology. International Journal of Human- Computer Studies 65(2007), 569–582 (2007)Rubin, D.L., Shah, N.H., Noy, N.F.: Biomedical ontologies: a functional perspective. Briefings in bioinformatics 9(1), 75–90 (2007)Stevens, R., Egaña Aranguren, M., Wolstencroft, K., Sattler, U., Drummond, N., Horridge, M., Rector, A.: Using OWL to model biological knowledge. International Journal of Human-Computer Studies 65(2007), 583–594 (2007)Park, S., Lee, J.K.: Rule identification using ontology while acquiring rules from Web pages. International Journal of Human-Computer Studies 65(2007), 644–658 (2007)Clark, K.L., McCabe, F.G.: Ontology schema for an agent belief store. International Journal of Human-Computer Studies 65(2007), 625–643 (2007)Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5(2), 199–220 (1993)Franco, C., Bengtsson, B., Johannsson, G.: The GH/IGF-1 Axis in Obesity: Physiological and Pathological aspects. Metabolic syndrome and Related Disorders 4, 51–56 (2006

Psychophysiological analysis of a pedagogical agent and robotic peer for individuals with autism spectrum disorders.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by ongoing problems in social interaction and communication, and engagement in repetitive behaviors. According to Centers for Disease Control and Prevention, an estimated 1 in 68 children in the United States has ASD. Mounting evidence shows that many of these individuals display an interest in social interaction with computers and robots and, in general, feel comfortable spending time in such environments. It is known that the subtlety and unpredictability of people’s social behavior are intimidating and confusing for many individuals with ASD. Computerized learning environments and robots, however, prepare a predictable, dependable, and less complicated environment, where the interaction complexity can be adjusted so as to account for these individuals’ needs. The first phase of this dissertation presents an artificial-intelligence-based tutoring system which uses an interactive computer character as a pedagogical agent (PA) that simulates a human tutor teaching sight word reading to individuals with ASD. This phase examines the efficacy of an instructional package comprised of an autonomous pedagogical agent, automatic speech recognition, and an evidence-based instructional procedure referred to as constant time delay (CTD). A concurrent multiple-baseline across-participants design is used to evaluate the efficacy of intervention. Additionally, post-treatment probes are conducted to assess maintenance and generalization. The results suggest that all three participants acquired and maintained new sight words and demonstrated generalized responding. The second phase of this dissertation describes the augmentation of the tutoring system developed in the first phase with an autonomous humanoid robot which serves the instructional role of a peer for the student. In this tutoring paradigm, the robot adopts a peer metaphor, where its function is to act as a peer. With the introduction of the robotic peer (RP), the traditional dyadic interaction in tutoring systems is augmented to a novel triadic interaction in order to enhance the social richness of the tutoring system, and to facilitate learning through peer observation. This phase evaluates the feasibility and effects of using PA-delivered sight word instruction, based on a CTD procedure, within a small-group arrangement including a student with ASD and the robotic peer. A multiple-probe design across word sets, replicated across three participants, is used to evaluate the efficacy of intervention. The findings illustrate that all three participants acquired, maintained, and generalized all the words targeted for instruction. Furthermore, they learned a high percentage (94.44% on average) of the non-target words exclusively instructed to the RP. The data show that not only did the participants learn nontargeted words by observing the instruction to the RP but they also acquired their target words more efficiently and with less errors by the addition of an observational component to the direct instruction. The third and fourth phases of this dissertation focus on physiology-based modeling of the participants’ affective experiences during naturalistic interaction with the developed tutoring system. While computers and robots have begun to co-exist with humans and cooperatively share various tasks; they are still deficient in interpreting and responding to humans as emotional beings. Wearable biosensors that can be used for computerized emotion recognition offer great potential for addressing this issue. The third phase presents a Bluetooth-enabled eyewear – EmotiGO – for unobtrusive acquisition of a set of physiological signals, i.e., skin conductivity, photoplethysmography, and skin temperature, which can be used as autonomic readouts of emotions. EmotiGO is unobtrusive and sufficiently lightweight to be worn comfortably without interfering with the users’ usual activities. This phase presents the architecture of the device and results from testing that verify its effectiveness against an FDA-approved system for physiological measurement. The fourth and final phase attempts to model the students’ engagement levels using their physiological signals collected with EmotiGO during naturalistic interaction with the tutoring system developed in the second phase. Several physiological indices are extracted from each of the signals. The students’ engagement levels during the interaction with the tutoring system are rated by two trained coders using the video recordings of the instructional sessions. Supervised pattern recognition algorithms are subsequently used to map the physiological indices to the engagement scores. The results indicate that the trained models are successful at classifying participants’ engagement levels with the mean classification accuracy of 86.50%. These models are an important step toward an intelligent tutoring system that can dynamically adapt its pedagogical strategies to the affective needs of learners with ASD

e-Health sensor platform: Diseño e implementación de una plataforma sensorial biométrica para diagnóstico de pacientes en tiempo real y otras aplicaciones médicas

Este proyecto está enmarcado dentro de mis prácticas en la empresa Libelium Comunicaciones Distribuidas S.L. Su motivación surge del interés en la creación de un dispositivo sensorial de parámetros biométricos que le permita utilizar esta tecnología, actualmente demasiado cara, a todo el mundo. Las redes sensoriales inalámbricas están formadas por una serie de nodos que miden parámetros de interés mediante sensores, y trabajan en conjunto para enviar esta información. La instalación de una red sensorial en el entorno de un paciente o persona con limitaciones, posibilita una atención y control constante, incluso en su propio domicilio. Para este proyecto se decide trabajar sobre la plataforma Open Source Arduino. Siguiendo las líneas de ese dispositivo, el proyecto se apoyará en las bases definidas por los productos del movimiento Open Source: contenido libre, accesibilidad, bajo coste... Por lo tanto, se pretende integrar en un único dispositivo una serie de sensores biométricos, para posibilitar la monitorización de parámetros vitales. Este seguimiento tiene que ser en tiempo real, de manera que es conocido el estado del sujeto y sus posibles necesidades. El campo de aplicación incluye todo tipo de monitorización de pacientes de forma poco invasiva, y otros usos que dependan de mediciones biomédicas. El primer paso consistirá en la búsqueda de las necesidades del usuario, investigación de sistemas ya existentes, y estudio de sensores en el mercado. Esto nos permitirá definir unos requisitos mínimos de la plataforma, con los que poder continuar trabajando. Una vez definidos los sensores se deben diseñar las diferentes etapas, el hardware formado por la electrónica de adaptación necesaria para los sensores elegidos. Con respecto al software, se implementará una librería con múltiples funciones y ejemplos, con el fin de facilitar su programación al usuario final. El resultado final pretende ser un dispositivo real, que se pueda comercializar como un producto acabado y funcional, acercando la tecnología de la monitorización médica a todos los lugares del planeta a un precio asequible, y que sirva como base para un futuro producto utilizable como "mini hospital" o centro de diagnóstico médico de bajo coste en países en vías de desarrollo o subdesarrollados. Aplicable al campo de la telemedicina, se busca revolucionar esta tecnología, rompiendo con la privatización de este mercado y disminuyendo el precio del producto final en comparación con los prohibitivos precios de los dispositivos hospitalarios. Esto abrirá las puertas a un nuevo movimiento de tecnologías médicas libres

Technology-infused learning environments to support the development of empathy

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 190-202).This dissertation explores how technology-infused learning environments can be designed to support the development of empathy for others, and contains contributions across the theoretical, design, and empirical dimensions. From a theoretical perspective, Empathy Development Environments have been defined as technology-infused learning environments to support the cultivation of empathy. I have also developed a framework called Trajectories of Awareness that can be used as a guide for structuring activities to cultivate empathy through the simultaneous exploration of emotion and identity within a learning environment. This exploration takes place by first focusing on self and eventually moving into an understanding of others. From the design aspect, a model Empathy Development Environment called Beyond the Looking has been created in order to operationalize the conceptual foundations. Further, a platform called Affect as Index has been envisioned and implemented for supporting conversations around emotion that were previously intangible. Empirically, three iterations of a design-based research study have been carried out as a means to flesh out a set of guidelines for the implementation of Empathy Development Environments. For each of the three iterations, challenges to the implementation were utilized to refine the design of the model environment to progress to the next iteration. These three iterations are analyzed based on a framework proposed for the design and analysis of Empathy Development Environments. Analysis revealed that the environment supported participants in establishing a community that allowed them to practice the skills of empathy.by Shaundra Bryant Daily.Ph.D

Affective Signals as Implicit Indicators of Information Relevancy and Information Processing Strategies

Search engines have become better in providing information to users, however, they still face major challenges such as determining how searchers process information, how they make relevance judgments, and how their cognitive or emotional state affect their search progress. We address these challenges by exploring searchers' affective dimension. In particular, we investigate how feelings, facial expressions, and electrodermal activity (EDA) could help to understand information relevancy, search progress, and information processing strategies (IPSs). To meet this goal, we designed an experiment with 45 participants exposed to affective stimuli prior solving a precision-oriented search task. Results indicate that initial affective states are linked to IPSs. In addition, we found that smiles act as implicit indicators of information relevancy and IPSs. Moreover, results convey that both smiles and EDA may serve as implicit indicators of progress and completion of search tasks. Findings from this work have practical implications in areas such as personalization and relevance feedback.ye