The application of humanoid robots is gaining attention as a solution to the caregiver shortage caused by an aging population. In this study, we automated the process of changing a patient’s body position from supine to lateral, a key aspect of nursing care. We proposed a method for recognizing a patient’s 3D posture at close range by simultaneously using a fisheye camera and a RGBD camera. For robot motion, we developed a trajectory generation method that adapts to the patient’s posture by converting measurement data into a mathematical model. Additionally, we identified the optimal timing for the movement of robot arms with minimal physical strain by considering human body dynamics. In all experiments using mannequins of different body shapes, the robot successfully reached the target joint and lifted one side of the body by more than 48 degrees. Future work will include detection of joints unaffected by body bulges and application the method to other repositioning movements.

This work presents FamilyScope, a sensor-based family informatics system that enables reflection upon family data collected from family activity scenarios (e.g., game playing and movie watching) that include affective aspects of a family's social interactions. We conducted a user study with ten families (n=30) in a smart home testbed to observe how our system supports data reflection of the affective and behavioral states among family members. Our findings showed that FamilyScope facilitated family data reflection on affective and behavioral aspects of family interactions. Overall, families reported that the system well reflected family members' general tendencies in terms of affective and behavioral responses and even helped them gain new insights about each other. Based on the findings, we provide practical design approaches for collective reflection in family informatics systems.

We explore design opportunities for using interactive technologies to enrich group fitness exercises, such as group spinning and swimming, in which an instructor guides a workout program and members synchronously perform a shared physical activity. As a case study, we investigate group fitness swimming. The design challenge is to coordinate a large group of people by considering trade-offs between social awareness and information overload. Our resulting group fitness swimming game, SwimTrain, allows a group of people to have localized synchronous interactions over a virtual space. The game uses competitive and cooperative phases to help group members acquire group-wide awareness. The results of our user study showed that SwimTrain provides socially-enriched swimming experiences, motivates swimmers to follow a training regimen and exert more intensely, and allows strategic game play dealing with skill differences among swimmers. Consequently, we propose several practical considerations for designing group fitness exergames.

Prolonged inactivity in office workers is a well-known contributor to various diseases, such as obesity, diabetes, and cardiovascular dysfunction. In recent years, active workstations that incorporate physical activities such as walking and cycling into the workplace have gained significant popularity, owing to the accessibility of the workouts they offer. While their efficacy is well documented in medical and physiological literature, research regarding the user experience of such systems has rarely been performed, despite its importance for interactive systems design. As a case study, we focus on active workstations that incorporate under desk elliptical trainers, and conduct controlled experiments regarding work performance and a four week long field deployment to explore user experience with 13 participants. We investigate how such workouts influence work performance, when and why workers work out during working hours, and the general feelings of workers regarding usage. Our experimental results indicate that while work performance is not influenced, the cognitive load of tasks critically influences workout decisions. Active workstations were alternatively used as mood enhancers, footrests, and for fidgeting, and there exist unique social and technical aspects to be addressed, such as noise issues and space constraints. Our results provide significant implications for the design of active workstations and interactive workplaces in general.

The unique aquatic nature of swimming makes it difficult to use social or technical strategies to mitigate the tediousness of monotonous exercises. In this study, we propose the use of a smartphone-based multiplayer exergame named MobyDick . MobyDick is designed to be played while swimming, where a team of swimmers collaborate to hunt down a virtual monster. To this end, we take into account both human factors and technical challenges under swimming contexts. First, we perform a comparative analysis of a variety of wireless networking technologies in the aquatic environment and identify various technical constraints on wireless networking. Second, we develop a swimming activity recognition system to enable precise and real-time game inputs. Third, we devise a multiplayer game design by employing the unique interaction mode viable in an underwater environment, where the abilities of human communication are highly limited. Finally, we prototype MobyDick on waterproof off-the-shelf Android phones, and we deploy it in real swimming pool environments ( n = 8). Our qualitative analysis of user interview data reveals certain unique aspects of multiplayer swimming games.

Document capturing with smartphone cameras is performed increasingly often in our daily lives. However, our user study results (n=10) showed that more than 80% of landscape tasks had incorrect orientations. To solve this problem, we systematically analyzed user behavior of document capturing and proposed a novel solution called ScanShot that detects document capturing moments to help users correct the orientation errors. ScanShot tracks the gravity direction to capture document capturing moments, analyzes logged gyroscope data to automatically update orientation changes, and provides visual feedback of the inferred orientation for manual correction. Our user study results (n=20) confirmed that capturing moments can be recognized with accuracy of 97.5%, our update mechanism can reduce the orientation errors by 59 percentage points.

The unique aquatic nature of swimming makes it very difficult to use social or technical strategies to mitigate the tediousness of monotonous exercises. In this study, we propose MobyDick, a smartphone-based multi-player exergame designed to be used while swimming, in which a team of swimmers collaborate to hunt down a virtual monster. In this paper, we present a novel, holistic game design that takes into account both human factors and technical challenges. Firstly, we perform a comparative analysis of a variety of wireless networking technologies in the aquatic environment and identify various technical constraints on wireless networking. Secondly, we develop a single phone-based inertial and barometric stroke activity recognition system to enable precise, real-time game inputs. Thirdly, we carefully devise a multi-player interaction mode viable in the underwater environment highly limiting the abilities of human communication. Finally, we prototype MobyDick on waterproof off-the-shelf Android phones, and deploy it to real swimming pool environments (n = 8). Our qualitative analysis of user interview data reveals certain unique aspects of multi-player swimming games.