Temitayo Olugbade

University College London | UCL · UCL Interaction Centre

Background Among the adaptations of movement consistently associated with disability in chronic pain, guarding is common. Based on previous work, we sought to understand better the constituents of guarding; we also used the concept of flow to explore the description of un/naturalness that emerged from physiotherapists' descriptions of movement in c...

Given the importance of affective touch in human interactions, technology designers are increasingly attempting to bring this modality to the core of interactive technology. Advances in haptics and touch-sensing technology have been critical to fostering interest in this area. In this survey, we review how affective touch is investigated to enhance...

There is a growing body of studies on applying deep learning to biometrics analysis. Certain circumstances, however, could impair the objective measures and accuracy of the proposed biometric data analysis methods. For instance, people with chronic pain (CP) unconsciously adapt specific body movements to protect themselves from injury or additional...

p>Chronic pain is a prevalent condition where fear of movement and pain interferes with everyday functioning. Yet, there is no open body movement dataset for people with chronic pain in everyday settings. Our EmoPain@Home dataset addresses this with capture from people with and without chronic pain in their homes, while they performed their routine...

p>Chronic pain is a prevalent condition where fear of movement and pain interferes with everyday functioning. Yet, there is no open body movement dataset for people with chronic pain in everyday settings. Our EmoPain@Home dataset addresses this with capture from people with and without chronic pain in their homes, while they performed their routine...

The use of multiple raters to label datasets is an established practice in affective computing. The principal goal is to reduce unwanted subjective bias in the labelling process. Unfortunately, this leads to the key problem of identifying a ground truth for training the affect recognition system. This problem becomes more relevant in a sparsely-cro...

Self-supervised learning has shown value for uncovering informative movement features for human activity recognition. However, there has been minimal exploration of this approach for affect recognition where availability of large labelled datasets is particularly limited. In this paper, we propose a P-STEMR (Parallel Space-Time Encoding Movement Re...

There is a growing body of studies on applying deep learning to biometrics analysis. Certain circumstances, however, could impair the objective measures and accuracy of the proposed biometric data analysis methods. For instance, people with chronic pain (CP) unconsciously adapt specific body movements to protect themselves from injury or additional...

While there is growing interest in developing tech-nology to support pain assessment, pain-related self-management, and healthcare personalisation, there are currently no datasets on nonverbal pain behaviour in the context of functional activities. To address this gap, we introduce the EmoPain(at)Home dataset which consists of motion capture data a...

Smart earables offer great opportunities for conducting ubiquitous computing research. This paper shares its reflection on collecting self-reports from runners using the microphone on the smart eSense earbud device. Despite the advantages of the eSense in allowing researchers to collect continuous voice self-reports anytime anywhere, it also captur...

Movement dataset reviews exist but are limited in coverage, both in terms of size and research discipline. While topic-specific reviews clearly have their merit, it is critical to have a comprehensive overview based on a systematic survey across disciplines. This enables higher visibility of datasets available to the research communities and can fo...

Pain is a ubiquitous and multifaceted experience, making the gath- ering of ground truth for training machine learning system partic- ularly difficult. In this paper, we reflect on the use of voice-based Experience Sampling Method (ESM) approaches for collecting pain self-reports in two different real-life case studies: long-distance run- ners, and...

We ran the first Affective Movement Recognition (AffectMove) challenge that brings together datasets of affective bodily behaviour across different real-life applications to foster work in this area. Research on automatic detection of naturalistic affective body expressions is still lagging behind detection based on other modalities whereas movemen...

Our daily human life is filled with a myriad of joint action moments, be it children playing, adults working together (i.e., team sports), or strangers navigating through a crowd. Joint action brings individuals (and embodiment of their emotions) together, in space and in time. Yet little is known about how individual emotions propagate through emb...

In chronic pain rehabilitation, physiotherapists adapt physical activity to patients’ performance based on their expression of protective behavior, gradually exposing them to feared but harmless and essential everyday activities. As rehabilitation moves outside the clinic, technology should automatically detect such behavior to provide similar supp...

In chronic pain rehabilitation, physiotherapists adapt physical activity to patients’ performance based on their expression of protective behavior, gradually exposing them to feared but harmless and essential everyday activities. As rehabilitation moves outside the clinic, technology should automatically detect such behavior as to provide similar p...

The EmoPain 2020 Challenge is the first international competition aimed at creating a uniform platform for the comparison of multi-modal machine learning and multimedia processing methods of chronic pain assessment from human expressive behaviour, and also the identification of pain-related behaviours. The objective of the challenge is to promote r...

The use of multiple clocks has been a favoured approach to modelling the multiple timescales of sequential data. Previous work based on clocks and multi-timescale studies in general have not clearly accounted for multidimensionality of data such that each dimension has its own timescale(s). Focusing on body movement data which has independent yet c...

We propose a novel neural network architecture, named the Global Workspace Network (GWN), which addresses the challenge of dynamic and unspecified uncertainties in multimodal data fusion. Our GWN is a model of attention across modalities and evolving through time, and is inspired by the well-established Global Workspace Theory from the field of cog...

For technology (like serious games) that aims to deliver interactive learning, it is important to address relevant mental experiences such as reflective thinking during problem solving. To facilitate research in this direction, we present the weDraw-1 Movement Dataset of body movement sensor data and reflective thinking labels for 26 children solvi...

We propose a novel neural network architecture, named the Global Workspace Network (GWN), that addresses the challenge of dynamic uncertainties in multimodal data fusion. The GWN is inspired by the well-established Global Workspace Theory from cognitive science. We implement it as a model of attention, between multiple modalities, that evolves thro...

The EmoPain 2020 Challenge is the first international competition aimed at creating a uniform platform for the comparison of machine learning and multimedia processing methods of automatic chronic pain assessment from human expressive behaviour, and also the identification of pain-related behaviours. The objective of the challenge is to promote res...

When developing children interaction systems, such as serious games in educational technology context, it is important to take into account and address relevant cognitive and emotional child's experiences that may influence learning outcomes. Some works were done to analyze and automatically recognize these cognitive and affective states from nonve...

For people with chronic pain, the assessment of protective behavior during physical functioning is essential to understand their subjective pain-related experiences (e.g., fear and anxiety toward pain and injury) and how they deal with such experiences (avoidance or reliance on specific body joints), with the ultimate goal of guiding intervention....

For people with chronic pain, the assessment of protective behavior during physical functioning is essential to understand their subjective pain-related experiences (e.g., fear and anxiety toward pain and injury) and how they deal with such experiences (avoidance or reliance on specific body joints), with the ultimate goal of guiding intervention....

In chronic pain physical rehabilitation, physiotherapists adapt exercise sessions according to the movement behavior of patients. As rehabilitation moves beyond clinical sessions, technology is needed to similarly assess movement behaviors and provide such personalized support. In this paper, as a first step, we investigate automatic detection of p...

Introduction: Pain-related behavior in people with chronic pain is often overlooked in a focus on increasing the amount of activity, yet it may limit activity and maintain pain and disability. Targeting it in treatment requires better understanding of the role of beliefs, emotion, and pain in pain behavior. Objectives: This study aimed to clarif...

For people with chronic pain (CP), the assessment of protective behavior during physical functioning is essential to understand their subjective pain-related experiences (e.g., fear and anxiety toward pain and injury) and how they deal with such experiences (avoidance or reliance on specific body joints), with the ultimate goal of guiding intervent...

Although clinical best practice suggests that affect awareness could enable more effective technological support for physical rehabilitation through personalisation to psychological needs, designers need to consider what affective states matter, and how they should be tracked and addressed. In this article, we set the standard by analysing how the...

For technology (like serious games) that aims to deliver interactive learning, it is important to address relevant mental experiences such as reflective thinking during problem solving. To facilitate research in this direction, we present the weDraw-1 Movement Dataset of body movement sensor data and reflective thinking labels for 26 children solvi...

Chronic pain is a prevalent disorder that affects engagement in valued activities. This is a consequence of cognitive and affective barriers, particularly low self-efficacy and emotional distress (i.e. fear/anxiety and depressed mood), to physical functioning. Although clinicians intervene to reduce these barriers, their support is limited to clini...

Clinicians tailor intervention in chronic pain rehabilitation to movement related self-efficacy (MRSE). This motivates us to investigate automatic MRSE estimation in this context towards the development of technology that is able to provide appropriate support in the absence of a clinician. We first explored clinical observer estimation, which show...

This paper discusses self-efficacy, curiosity, and reflectivity as cognitive and affective states that are critical to learning but are overlooked in the context of affect-aware technology for learning. This discussion sits within the opportunities offered by the weDRAW project aiming at an embodied approach to the design of technology to support e...

BACKGROUND Movement is an important aspect of life: it enables social interactions, household activities, employment, and physical fitness. In chronic musculoskeletal pain (CMP)–a prevalent medical condition where pain persists in the absence of tissue damage–wrong association of pain with movement and the accompanying fear of (re)injury lends to g...

Touch is a primary nonverbal communication channel used to communicate emotions or other social messages. Despite its importance, this channel is still very little explored in the affective computing field, as much more focus has been placed on visual and aural channels. In this paper, we investigate the possibility to automatically discriminate be...

People with chronic musculoskeletal pain would benefit from technology that provides run-time personalized feedback and help adjust their physical exercise plan. However, increased pain during physical exercise, or anxiety about anticipated pain increase, may lead to setback and intensified sensitivity to pain. Our study investigates the possibilit...

Physical activity is essential in chronic pain rehabilitation. However, anxiety due to pain or a perceived exacerbation of pain causes people to guard against beneficial exercise. Interactive rehabiliation technology sensitive to such behaviour could provide feedback to overcome such psychological barriers. To this end, we developed a Support Vecto...

Dementia is a growing healthcare problem, and it has become necessary to find a way to reduce the prevalence of this disease. Mild cognitive impairment is a risk factor for dementia, and being able to detect the onset of mild cognitive impairment gives healthcare professionals the chance to reduce the effect of dementia on the society. In this pape...