The objective of this work is to introduce Augmented and Mixed Reality technologies in aquatic leisure activities. We have proposed a new device which is autonomous, mobile and easily transportable by one person. It can also be easily installed, equipped with GPS and wireless systems, and has positive buoyancy. The device will be used at water surface as well as underwater using a tuba. Moreover, the device is equipped with one (can be upgraded for more) video camera pointing downwards. Augmented Reality contents combining actual underwater images with 3D animated images will be one of the preferred ways to use the device.

Serious games are a promising approach to improve gait rehabilitation for people with gait disorders. Combined with wearable augmented reality headset, serious games for gait rehabilitation in a clinical setting can be envisaged, allowing to evolve in a real environment and provide fun and feedback to enhance patient’s motivation. This requires a method to obtain accurate information on the spatiotemporal gait parameters of the playing patient. To this end, we propose a new algorithm called HoloStep that computes spatiotemporal gait parameters using only the head pose provided by an augmented reality headset (Hololens). It is based on the detection of peaks associated to initial contact event, and uses a combination of locking distance, locking time, peak amplitude detection with custom thresholds for children with CP. The performance of HoloStep was compared during a walking session at comfortable speed to Zeni’s reference algorithm, which is based on kinematics and a full 3D motion capture system. Our study included 62 children with cerebral palsy (CP), classified according to Gross Motor Function Classification System (GMFCS) between levels I and III, and 13 healthy participants (HP). Metrics such as sensitivity, specificity, accuracy and precision for step detection with HoloStep were above 96%. The Intra-Class Coefficient between steps length calculated with HoloStep and the reference was 0.92 (GMFCS I), 0.86 (GMFCS II/III) and 0.78 (HP). HoloStep demonstrated good performance when applied to a wide range of gait patterns, including children with CP using walking aids. Findings provide important insights for future gait intervention using augmented reality games for children with CP.

Motor rehabilitation exercises require recurrent repetitions to enhance patients’ gestures. However, these repetitive gestures usually decrease the patients’ motivation and stress them. Virtual Reality (VR) exer-games (serious games in general) could be an alternative solution to address the problem. This innovative technology encourages patients to train different gestures with less effort since they are totally immersed in an easy to play exer-game. Despite this evolution, patients, with available exer-games, still suffer in performing their gestures correctly without pain. The developed applications do not consider the patients psychological states when playing an exer-game. Therefore, we believe that is necessary to develop personalized and adaptive exer-games that take into consideration the patients’ emotions during rehabilitation exercises. This paper proposed a VR-PEER adaptive exer-game system based on emotion recognition. The platform contain three main modules: (1) computing and interpretation module, (2) emotion recognition module, (3) adaptation module. Furthermore, a virtual reality-based serious game is developed as a case study, that uses updated facial expression data and provides dynamically the patient’s appropriate game to play during rehabilitation exercises. An experimental study has been conducted on fifteen subjects who expressed the usefulness of the proposed system in motor rehabilitation process.

International audienceThe implementation of an interaction between a user and a Virtual Environment (VE) in Virtual Reality (VR) may use various techniques. However, in some cases, the interaction must be very precise and comfortable for the user. In this paper, we introduce a new selection and manipulation technique called FOLLOW-ME. The model associated to this technique splits the Virtual Environment into three zones in which a specificinteraction model is used: a free manipulation zone, a scaled manipulation zone and a precise manipulation zone. Each one of the three zones is characterized by a specific interaction granularity which defines the properties of the interaction in the concerned zone. This splitting is created in order to have both precision near the object to reach or to manipulate (scaled and precise manipulation zones) and to maintain a realistic and free interaction in the VE (free manipulation zone). In the precise manipulation zone, we use the concept of virtual guides in order to assist user. In this paper, we exhibit the formalization of the model associated to the FOLLOW-ME technique. Then, we both compare our technique with classical interaction techniques in the case of a task which consists in trying to reach an object in VE and give some insights about the conditions of usefulness of virtual guides in a selection task. Some preliminary experimental results are presented and discussed