201 citations · 489 across the 26 of their papers we have counts for
26 papers
Low-Back Pain Physical Rehabilitation by Movement Analysis in Clinical Trial
Sao Mai Nguyen
To allow the development and assessment of physical rehabilitation by an intelligent tutoring system, we propose a medical dataset of clinical patients carrying out low back-pain r…
The intrinsic motivation of reinforcement and imitation learning for sequential tasks
Sao Mai Nguyen
This work in the field of developmental cognitive robotics aims to devise a new domain bridging between reinforcement learning and imitation learning, with a model of the intrinsic…
Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity Recognition
Damien Bouchabou, Sao Mai Nguyen
Within the evolving landscape of smart homes, the precise recognition of daily living activities using ambient sensor data stands paramount. This paper not only aims to bolster exi…
Analyzing Data Efficiency and Performance of Machine Learning Algorithms for Assessing Low Back Pain Physical Rehabilitation Exercises
Aleksa Marusic, Louis Annabi, Sao Msi Nguyen +1
Analyzing human motion is an active research area, with various applications. In this work, we focus on human motion analysis in the context of physical rehabilitation using a robo…
A Medical Low-Back Pain Physical Rehabilitation Dataset for Human Body Movement Analysis
Sao Mai Nguyen, Maxime Devanne, Olivier Remy-Neris +2
While automatic monitoring and coaching of exercises are showing encouraging results in non-medical applications, they still have limitations such as errors and limited use context…
Unsupervised Motion Retargeting for Human-Robot Imitation
Louis Annabi, Ziqi Ma, Sao Mai Nguyen
This early-stage research work aims to improve online human-robot imitation by translating sequences of joint positions from the domain of human motions to a domain of motions achi…
Goal Space Abstraction in Hierarchical Reinforcement Learning via Reachability Analysis
Mehdi Zadem, Sergio Mover, Sao Mai Nguyen
Open-ended learning benefits immensely from the use of symbolic methods for goal representation as they offer ways to structure knowledge for efficient and transferable learning. H…
Goal Space Abstraction in Hierarchical Reinforcement Learning via Set-Based Reachability Analysis
Mehdi Zadem, Sergio Mover, Sao Mai Nguyen
Open-ended learning benefits immensely from the use of symbolic methods for goal representation as they offer ways to structure knowledge for efficient and transferable learning. H…
Robots Learn Increasingly Complex Tasks with Intrinsic Motivation and Automatic Curriculum Learning
Sao Mai Nguyen, Nicolas Duminy, Alexandre Manoury +2
Multi-task learning by robots poses the challenge of the domain knowledge: complexity of tasks, complexity of the actions required, relationship between tasks for transfer learning…
Human Activity Recognition (HAR) in Smart Homes
Damien Bouchabou, Christophe Lohr, Ioannis Kanellos +1
Generally, Human Activity Recognition (HAR) consists of monitoring and analyzing the behavior of one or more persons in order to deduce their activity. In a smart home context, the…
Using Language Model to Bootstrap Human Activity Recognition Ambient Sensors Based in Smart Homes
Damien Bouchabou, Sao Mai Nguyen, Christophe Lohr +2
Long Short Term Memory LSTM-based structures have demonstrated their efficiency for daily living recognition activities in smart homes by capturing the order of sensor activations…
A co-design approach for a rehabilitation robot coach for physical rehabilitation based on the error classification of motion errors
Maxime Devanne, Sao Mai Nguyen, Olivier Rémy-Néris +3
The rising number of the elderly incurs growing concern about healthcare, and in particular rehabilitation healthcare. Assistive technology and assistive robotics in particular may…
A Survey of Human Activity Recognition in Smart Homes Based on IoT Sensors Algorithms: Taxonomies, Challenges, and Opportunities with Deep Learning
Damien Bouchabou, Sao Mai Nguyen, Christophe Lohr +2
Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of sensors have encouraged the development of smart environments, such as smart homes. Smart…
Intrinsically Motivated Open-Ended Multi-Task Learning Using Transfer Learning to Discover Task Hierarchy
Nicolas Duminy, Sao Mai Nguyen, Junshuai Zhu +2
In open-ended continuous environments, robots need to learn multiple parameterised control tasks in hierarchical reinforcement learning. We hypothesise that the most complex tasks…
Fully Convolutional Network Bootstrapped by Word Encoding and Embedding for Activity Recognition in Smart Homes
Damien Bouchabou, Sao Nguyen, Christophe Lohr +2
Activity recognition in smart homes is essential when we wish to propose automatic services for the inhabitants. However, it poses challenges in terms of variability of the environ…
Hierarchical Affordance Discovery using Intrinsic Motivation
Alexandre Manoury, Sao Mai Nguyen, Cédric Buche
To be capable of lifelong learning in a real-life environment, robots have to tackle multiple challenges. Being able to relate physical properties they may observe in their environ…
How An Automated Gesture Imitation Game Can Improve Social Interactions With Teenagers With ASD
Linda Nanan Vallée, Sao Mai Nguyen, Christophe Lohr +2
With the outlook of improving communication and social abilities of people with ASD, we propose to extend the paradigm of robot-based imitation games to ASD teenagers. In this pape…
Building an Automated Gesture Imitation Game for Teenagers with ASD
Linda Nanan Vallée, Christophe Lohr, Sao Mai Nguyen +2
Autism spectrum disorder is a neurodevelopmental condition that includes issues with communication and social interactions. People with ASD also often have restricted interests and…
An implementation of an imitation game with ASD children to learn nursery rhymes
Sao Mai Nguyen, Nathalie Collot-Lavenne, Christophe Lohr +6
Previous studies have suggested that being imitated by an adult is an effective intervention with children with autism and developmental delay. The purpose of this study is to inve…
Generating Shared Latent Variables for Robots to Imitate Human Movements and Understand their Physical Limitations
Maxime Devanne, Sao Mai Nguyen
Assistive robotics and particularly robot coaches may be very helpful for rehabilitation healthcare. In this context, we propose a method based on Gaussian Process Latent Variable…
Learning a Set of Interrelated Tasks by Using Sequences of Motor Policies for a Strategic Intrinsically Motivated Learner
Nicolas Duminy, Sao Mai Nguyen, Dominique Duhaut
We propose an active learning architecture for robots, capable of organizing its learning process to achieve a field of complex tasks by learning sequences of motor policies, calle…
Socially Guided Intrinsic Motivation for Robot Learning of Motor Skills
Sao Mai Nguyen, Pierre-Yves Oudeyer
This paper presents a technical approach to robot learning of motor skills which combines active intrinsically motivated learning with imitation learning. Our architecture, called…
Active choice of teachers, learning strategies and goals for a socially guided intrinsic motivation learner
Sao Mai Nguyen, Pierre-Yves Oudeyer
We present an active learning architecture that allows a robot to actively learn which data collection strategy is most efficient for acquiring motor skills to achieve multiple out…
Real-time face swapping as a tool for understanding infant self-recognition
Sao Mai Nguyen, Masaki Ogino, Minoru Asada
To study the preference of infants for contingency of movements and familiarity of faces during self-recognition task, we built, as an accurate and instantaneous imitator, a real-t…