Skip to main content

Research Repository

Advanced Search

All Outputs (43)

Identifying Variation in the Newborn Life Support Procedure: An Automated Method (2023)
Conference Proceeding
Tan, A., Remenyte-Prescott, R., Egede, J., Valstar, M., & Sharkey, D. (2023). Identifying Variation in the Newborn Life Support Procedure: An Automated Method. In M. P. Brito, T. Aven, P. Baraldi, M. Čepin, & E. Zio (Eds.), Proceedings of the 33rd European Safety and Reliability Conference (ESREL 2023) (607-614)

This research is conducted for developing an automated method to recognize variations in the Newborn Life Support (NLS) procedure. Compliance with the NLS standard guideline is essential to prevent any adverse consequences for the newborn. Video reco... Read More about Identifying Variation in the Newborn Life Support Procedure: An Automated Method.

A modelling approach to studying variations in newborn life support procedure (2023)
Journal Article
Tan, A., Remenyte-Prescott, R., Valstar, M., & Sharkey, D. (2023). A modelling approach to studying variations in newborn life support procedure. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, https://doi.org/10.1177/1748006X231173595

Variations in clinical practice are common. However, some variations may cause undesired consequences. Careful consideration of their causes and effects is necessary to assure the quality of healthcare delivery. A modelling approach that could captur... Read More about A modelling approach to studying variations in newborn life support procedure.

Benchmarking framework for machine learning classification from fNIRS data (2023)
Journal Article
Benerradi, J., Clos, J., Landowska, A., Valstar, M. F., & Wilson, M. L. (2023). Benchmarking framework for machine learning classification from fNIRS data. Frontiers in Neuroergonomics, 4, Article 994969. https://doi.org/10.3389/fnrgo.2023.994969

Background: While efforts to establish best practices with functional near infrared spectroscopy (fNIRS) signal processing have been published, there are still no community standards for applying machine learning to fNIRS data. Moreover, the lack of... Read More about Benchmarking framework for machine learning classification from fNIRS data.

Design and Evaluation of Virtual Human Mediated Tasks for Assessment of Depression and Anxiety (2021)
Conference Proceeding
Egede, J. O., Jaiswal, S., Galvez Trigo, M. J., Price, D., Elliot, N., Nixon, N., …Valstar, M. (2021). Design and Evaluation of Virtual Human Mediated Tasks for Assessment of Depression and Anxiety. In IVA '21: Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents (52-59). https://doi.org/10.1145/3472306.3478361

Virtual human technologies are now being widely explored as therapy tools for mental health disorders including depression and anxiety. These technologies leverage the ability of the virtual agents to engage in naturalistic social interactions with a... Read More about Design and Evaluation of Virtual Human Mediated Tasks for Assessment of Depression and Anxiety.

Designing an Adaptive Embodied Conversational Agent for Health Literacy: a User Study (2021)
Conference Proceeding
Egede, J., Galvez Trigo, M. J., Hazzard, A., Porcheron, M., Bodiaj, E., Fischer, J. E., …Valstar, M. (2021). Designing an Adaptive Embodied Conversational Agent for Health Literacy: a User Study. In IVA '21: Proceedings of the 21st ACM International Conference on Intelligent Virtual Agents (112-119). https://doi.org/10.1145/3472306.3478350

Access to healthcare advice is crucial to promote healthy societies. Many factors shape how access might be constrained, such as economic status, education or, as the COVID-19 pandemic has shown, remote consultations with health practitioners. Our wo... Read More about Designing an Adaptive Embodied Conversational Agent for Health Literacy: a User Study.

ALTCAI: Enabling the Use of Embodied Conversational Agents to Deliver Informal Health Advice during Wizard of Oz Studies (2021)
Conference Proceeding
Galvez Trigo, M. J., Porcheron, M., Egede, J., Fischer, J. E., Hazzard, A., Greenhalgh, C., …Valstar, M. (2021). ALTCAI: Enabling the Use of Embodied Conversational Agents to Deliver Informal Health Advice during Wizard of Oz Studies. In Proceedings of CUI 2021 : Conversational User Interfaces. https://doi.org/10.1145/3469595.3469621

We present ALTCAI, a Wizard of Oz Embodied Conversational Agent that has been developed to explore the use of interactive agents as an effective and engaging tool for delivering health and well-being advice to expectant and nursing mothers in Nigeria... Read More about ALTCAI: Enabling the Use of Embodied Conversational Agents to Deliver Informal Health Advice during Wizard of Oz Studies.

NottReal: A Tool for Voice-based Wizard of Oz studies (2020)
Conference Proceeding
Porcheron, M., Fischer, J. E., & Valstar, M. (2020). NottReal: A Tool for Voice-based Wizard of Oz studies. In CUI '20: Proceedings of the 2nd Conference on Conversational User Interfaces (1–3). https://doi.org/10.1145/3405755.3406168

We present NottReal, an application designed for simulating Voice User Interfaces (VUIs) in Wizard of Oz studies. We briefly discuss the premise and advantages of the Wizard of Oz method before moving onto introducing the design of the application, w... Read More about NottReal: A Tool for Voice-based Wizard of Oz studies.

Spectral Representation of Behaviour Primitives for Depression Analysis (2020)
Journal Article
Song, S., Jaiswal, S., Shen, L., & Valstar, M. (2020). Spectral Representation of Behaviour Primitives for Depression Analysis. IEEE Transactions on Affective Computing, https://doi.org/10.1109/taffc.2020.2970712

Depression is a serious mental disorder affecting millions of people. Traditional clinical diagnosis methods are subjective, complicated and require extensive participation of clinicians. Recent advances in automatic depression analysis systems promi... Read More about Spectral Representation of Behaviour Primitives for Depression Analysis.

Clinical Scene Segmentation with Tiny Datasets (2019)
Conference Proceeding
Smith, T. J., Sharkey, D., Crowe, J., & Valstar, M. (2019). Clinical Scene Segmentation with Tiny Datasets. In 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) (1637-1645). https://doi.org/10.1109/ICCVW.2019.00203

Many clinical procedures could benefit from automatic scene segmentation and subsequent action recognition. Using Convolutional Neural Networks to semantically segment meaningful parts of an image or video is still an unsolved problem. This becomes e... Read More about Clinical Scene Segmentation with Tiny Datasets.

Dynamic Facial Models for Video-Based Dimensional Affect Estimation (2019)
Conference Proceeding
Song, S., Sánchez-Lozano, E., Kumar Tellamekala, M., Shen, L., Johnston, A., & Valstar, M. (2019). Dynamic Facial Models for Video-Based Dimensional Affect Estimation. In Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) (1608-1617). https://doi.org/10.1109/ICCVW.2019.00200

Dimensional affect estimation from a face video is a challenging task, mainly due to the large number of possible facial displays made up of a set of behaviour primitives including facial muscle actions. The displays vary not only in composition but... Read More about Dynamic Facial Models for Video-Based Dimensional Affect Estimation.

Postnatal gestational age estimation of newborns using Small Sample Deep Learning (2018)
Journal Article
Torres Torres, M., Valstar, M., Henry, C., Ward, C., & Sharkey, D. (2019). Postnatal gestational age estimation of newborns using Small Sample Deep Learning. Image and Vision Computing, 83-84, 87-99. https://doi.org/10.1016/j.imavis.2018.09.003

© 2018 A baby's gestational age determines whether or not they are premature, which helps clinicians decide on suitable post-natal treatment. The most accurate dating methods use Ultrasound Scan (USS) machines, but these are expensive, require traine... Read More about Postnatal gestational age estimation of newborns using Small Sample Deep Learning.

Noise Invariant Frame Selection: A Simple Method to Address the Background Noise Problem for Text-independent Speaker Verification (2018)
Conference Proceeding
Song, S., Zhang, S., Schuller, B. W., Shen, L., & Valstar, M. (2018). Noise Invariant Frame Selection: A Simple Method to Address the Background Noise Problem for Text-independent Speaker Verification. In Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN). https://doi.org/10.1109/IJCNN.2018.8489497

The performance of speaker-related systems usually degrades heavily in practical applications largely due to the presence of background noise. To improve the robustness of such systems in unknown noisy environments, this paper proposes a simple pre-p... Read More about Noise Invariant Frame Selection: A Simple Method to Address the Background Noise Problem for Text-independent Speaker Verification.

A Functional Regression Approach to Facial Landmark Tracking (2018)
Journal Article
Sánchez-Lozano, E., Tzimiropoulos, G., Martinez, B., De la Torre, F., & Valstar, M. (2018). A Functional Regression Approach to Facial Landmark Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40(9), 2037-2050. https://doi.org/10.1109/TPAMI.2017.2745568

© 1979-2012 IEEE. Linear regression is a fundamental building block in many face detection and tracking algorithms, typically used to predict shape displacements from image features through a linear mapping. This paper presents a Functional Regressio... Read More about A Functional Regression Approach to Facial Landmark Tracking.

Digital innovations in L2 motivation: harnessing the power of the Ideal L2 Self (2018)
Journal Article
Adolphs, S., Clark, L., Dörnyei, Z., Glover, T., Henry, A., Muir, C., …Valstar, M. (in press). Digital innovations in L2 motivation: harnessing the power of the Ideal L2 Self. System, https://doi.org/10.1016/j.system.2018.07.014

Sustained motivation is crucial to learning a second language (L2), and one way to support this can be through the mental visualisation of ideal L2 selves (Dörnyei & Kubanyiova, 2014). This paper reports on an exploratory study which investigated the... Read More about Digital innovations in L2 motivation: harnessing the power of the Ideal L2 Self.

Human behaviour-based automatic depression analysis using hand-crafted statistics and deep learned spectral features (2018)
Conference Proceeding
Song, S., Shen, L., & Valstar, M. (2018). Human behaviour-based automatic depression analysis using hand-crafted statistics and deep learned spectral features. In Proceedings - 13th IEEE International Conference on Automatic Face and Gesture Recognition: FG2018: 15-19 May 2018 Xi'an, China (158-165). https://doi.org/10.1109/FG.2018.00032

Depression is a serious mental disorder that affects millions of people all over the world. Traditional clinical diagnosis methods are subjective, complicated and need extensive participation of experts. Audio-visual automatic depression analysis sys... Read More about Human behaviour-based automatic depression analysis using hand-crafted statistics and deep learned spectral features.

Predicting folds in poker using action unit detectors and decision trees (2018)
Conference Proceeding
Vinkemeier, D., Valstar, M., & Gratch, J. (2018). Predicting folds in poker using action unit detectors and decision trees. In Proceedings - 13th IEEE International Conference on Automatic face and Gesture Recognition: FG 2018 (504-511). https://doi.org/10.1109/FG.2018.00081

Predicting how a person will respond can be very useful, for instance when designing a strategy for negotiations. We investigate whether it is possible for machine learning and computer vision techniques to recognize a person’s intentions and predic... Read More about Predicting folds in poker using action unit detectors and decision trees.

The NoXi database: multimodal recordings of mediated novice-expert interactions (2017)
Conference Proceeding
Cafaro, A., Wagner, J., Baur, T., Dermouche, S., Torres, M. T., Pelachaud, C., …Valstar, M. F. (2017). The NoXi database: multimodal recordings of mediated novice-expert interactions.

We present a novel multi-lingual database of natural dyadic novice-expert interactions, named NoXi, featuring screen-mediated dyadic human interactions in the context of information exchange and retrieval. NoXi is designed to provide spontaneous inte... Read More about The NoXi database: multimodal recordings of mediated novice-expert interactions.

Cumulative attributes for pain intensity estimation (2017)
Conference Proceeding
Joy, E., & Valstar, M. (2017). Cumulative attributes for pain intensity estimation. In ICMI 2017 - Proceedings of the 19th ACM International Conference on Multimodal Interaction (146-153). https://doi.org/10.1145/3136755.3136789

Pain estimation from face video is a hard problem in automatic behaviour understanding. One major obstacle is the difficulty of collecting sufficient amounts of data, with balanced amounts of data for all pain intensity levels. To overcome this, we p... Read More about Cumulative attributes for pain intensity estimation.

AVEC 2017--Real-life depression, and affect recognition workshop and challenge (2017)
Conference Proceeding
Ringeval, F., Schuller, B., Valstar, M., Gratch, J., Cowie, R., Scherer, S., …Pantic, M. (2017). AVEC 2017--Real-life depression, and affect recognition workshop and challenge.

The Audio/Visual Emotion Challenge and Workshop (AVEC 2017) “Real-life depression, and affect” will be the seventh competition event aimed at comparison of multimedia processing and machine learning methods for automatic audiovisual depression and em... Read More about AVEC 2017--Real-life depression, and affect recognition workshop and challenge.

Automatic analysis of facial actions: a survey (2017)
Journal Article
Martinez, B., Valstar, M. F., Jiang, B., & Pantic, M. (2017). Automatic analysis of facial actions: a survey. IEEE Transactions on Affective Computing, https://doi.org/10.1109/TAFFC.2017.2731763

As one of the most comprehensive and objective ways to describe facial expressions, the Facial Action Coding System (FACS) has recently received significant attention. Over the past 30 years, extensive research has been conducted by psychologists and... Read More about Automatic analysis of facial actions: a survey.