Towards Emotional Interaction: Using Movies to Automatically Learn Users' Emotional States

The HCI community is actively seeking novel methodologies to gain insight into the user’s experience during interaction with both the application and the content. We propose an emotional recognition engine capable of automatically recognizing a set of human emotional states using psychophysiological measures of the autonomous nervous system, including galvanic skin response, respiration, and heart rate. A novel pattern recognition system, based on discriminant analysis and support vector machine classifiers is trained using movies’ scenes selected to induce emotions ranging from the positive to the negative valence dimension, including happiness, anger, disgust, sadness, and fear. In this paper we introduce an emotion recognition system and evaluate its accuracy by presenting the results of an experiment conducted with three physiologic sensors.

Ambient assisted living technology: comparative perspectives of users and caregivers

Developed societies are currently facing severe demographic changes: the world population is ageing at an unprecedented rate. This demographic trend will be also followed by an increase of people with physical limitations. New challenges are being raised to the traditional health care systems, not only in Portugal, but also in all other European states. There is an urgent need to find solutions that allow extending the time people can live in their preferred environment by increasing their autonomy, self-confidence and mobility. AAL4ALL is a project currently being developed in cooperation with 34 Portuguese interdisciplinary partners, from industry to academia, R&D and social disciplines, which employs a novel conceptual approach through the development of an ecosystem of products and services for Ambient Assisted Living (AAL) associated to a business model and validated through large scale trial. This paper presents a comparative perspective of the needs and attitudes towards technology of the AAL users and caregivers identified in the analysis of a set of three different surveys: a users survey targeted at the Portuguese seniors and pre-seniors; an informal caregivers survey targeted at the family, friends and neighbours who provide care without any financial compensation; and a formal caregivers survey targeted at physicians, nurses,psychologists, social workers, and direct-care workers providing care to elders. The first results indicate that AAL solutions must be affordable,user friendly and have a true perceived benefit to their users.

An ecosystem of products and systems for ambient intelligence – the AAL4ALL users perspective

Developed societies are currently facing severe demographic changes: the world is getting older at an unprecedented rate. In 2000, about 420 million people, or approximately 7 percent of the world population, were aged 65 or older. By 2050, that number will be nearly 1.5 billion people, about 16 percent of the world population. This demographic trend will be also followed by an increase of people with physical limitations. New challenges will be raised to the traditional health care systems, not only in Portugal, but also in all other European states. There is an urgent need to find solutions that allow extending the time people can live in their preferred environment by increasing their autonomy, self-confidence and mobility. AAL4ALL presents an idea for an answer through the development of an ecosystem of products and services for Ambient Assisted Living (AAL) associated to a business model and validated through large scale trial. This paper presents the results of the first survey developed within the AAL4ALL project: the users’ survey targeted at the Portuguese seniors and pre-seniors. This paper is, thus, about the lives of the Portuguese population aged 50 and over.

A laparoscopic surgery training interface

Laparoscopy is a surgical procedure on which operations in the abdomen are performed through small incisions using several specialized instruments. The laparoscopic surgery success greatly depends on surgeon skills and training. To achieve these technical high-standards, different apprenticeship methods have been developed, many based on in vivo training, an approach that involves high costs and complex setup procedures. This paper explores Virtual Reality (VR) simulation as an alternative for novice surgeons training. Even though several simulators are available on the market claiming successful training experiences, their use is extremely limited due to the economic costs involved. In this work, we present a low-cost laparoscopy simulator able to monitor and assist the trainee’s surgical movements. The developed prototype consists of a set of inexpensive sensors, namely an accelerometer, a gyroscope, a magnetometer and a flex sensor, attached to specific laparoscopic instruments. Our approach allows repeated assisted training of an exercise, without time constraints or additional costs, since no human artificial model is needed. A case study of our simulator applied to instrument manipulation practice (hand-eye coordination) is also presented.

Hand-held robotic device for laparoscopic surgery and training

Laparoscopic surgery (LS) has revolutionized traditional surgical techniques introducing minimally invasive procedures for diagnosis and local therapies. LSs have undeniable advantages, such as small patient incisions, reduced postoperative pain and faster recovery. On the other hand, restricted vision of the anatomical target, difficult handling of the surgical instruments, restricted mobility inside the human body, need of dexterity to hand-eye coordination and inadequate and non-ergonomic surgical instruments may restrict LS only to more specialized surgeons. To overcome the referred limitations, this work presents a new robotic surgical handheld system – the EndoRobot. The EndoRobot was designed to be used in clinical practice or even as a surgical simulator. It integrates an electromechanical system with 3 degrees of freedom. Each degree can be manipulated independently and combined with different levels of sensitivity allowing fast and slow movements. As other features, the EndoRobot has battery power or external power supply, enables the use of bipolar radiofrequency to prevent bleeding while cutting and allows plug-and-play of the laparoscopic forceps for rapid exchange. As a surgical simulator, the system was also instrumented to measure and transmit, in real time, its position and orientation for a training software able to monitor and assist the trainee’s surgical movements.

Application of Gage R&R methodology for improving the training and evaluation of automatic optical inspection machine operators

The current level of demand by customers in the electronics industry requires the production of parts with an extremely high level of reliability and quality to ensure complete confidence on the end customer. Automatic Optical Inspection (AOI) machines have an important role in the monitoring and detection of errors during the manufacturing process for printed circuit boards. These machines present images of products with probable assembly mistakes to an operator and him decide whether the product has a real defect or if in turn this was an automated false detection. Operator training is an important aspect for obtaining a lower rate of evaluation failure by the operator and consequently a lower rate of actual defects that slip through to the following processes. The Gage R&R methodology for attributes is part of a Six Sigma strategy to examine the repeatability and reproducibility of an evaluation system, thus giving important feedback on the suitability of each operator in classifying defects. This methodology was already applied in several industry sectors and services at different processes, with excellent results in the evaluation of subjective parameters. An application for training operators of AOI machines was developed, in order to be able to check their fitness and improve future evaluation performance. This application will provide a better understanding of the specific training needs for each operator, and also to accompany the evolution of the training program for new components which in turn present additional new difficulties for the operator evaluation. The use of this application will contribute to reduce the number of defects misclassified by the operators that are passed on to the following steps in the productive process. This defect reduction will also contribute to the continuous improvement of the operator evaluation performance, which is seen as a quality management goal.