Early prototype (2025)
Mobile Companion App
Self-reporting, emotion visualisations, contextual journaling, and insights — all on your phone.
Turn on emotion awareness. Take back control.
Anxiety disorders affect 1 in 10 people in the UK. MEMoPAD uses wearable devices to monitor emotions. It is designed to help people notice and interrupt anxiety loops, and have better conversations with clinicians.
Now: Phase VI (real-world use) under way, followed by the PhD thesis.
Clinicians and carers: you can still take part.
As seen in
What
Wearable emotion monitoring for anxiety disorders
Evidence
Patients, carers and clinicians involved across 7 co-design phases, 10–25 participants per phase
Funding
3.5-year PhD scholarship + £10,500 competitive funding
How Emotion Monitoring Helps Anxiety Disorders
- Continuous tracking: Captures patterns missed by self-report questionnaires
- Real-world context: Links emotions to daily activities, triggers, and coping strategies
- Objective data: Reduces recall bias and provides physiological evidence for clinical conversations
- Early intervention: Supports self-awareness, proactiveness and timely interventions
- Personalized insights: Recognizes individual patterns and multimodal data correlations
Why MEMoPAD Exists
Previous attempts to integrate structured data in mental health have faced persistent challenges: multimodal data is complex to interpret, social stigma delays help-seeking, and poor user engagement leads to high dropout rates.
MEMoPAD addresses this by focusing on emotion as a universal common ground. We combine passive physiological sensing from consumer wearables with active self-reporting through a companion mobile app, creating contextualised, longitudinal data that is meaningful to both users and their clinicians.
The system is co-designed from the ground up with people living with anxiety disorders, unpaid carers, and mental health clinicians. The goal: clear, continuous, interpretable emotion data that helps people understand themselves, manage their wellbeing proactively, and have deeper conversations with their care team.
See MEMoPAD in Action
Explore the prototype ecosystem: the mobile companion app, the wearable sensing hardware, and the clinician web dashboard. The app and dashboard demos show the early 2025 prototype; the current version reflects feedback from co-design Phases IV and V.
Wearable Sensing
Google Pixel Watch 2: heart rate (PPG) and movement in daily use (Phase VI), plus electrodermal activity and skin temperature in our lab study (Phase V). Milbotix SmartSocks provide a parallel physiological sensing pathway.
Early prototype (2025)
Clinician Web Dashboard
Navigate the clinician-facing dashboard. Click the image to explore the interactive prototype.
What Makes MEMoPAD Different
- Emotion as Common Ground: A four-colour vocabulary, Emotion Hues, co-designed to be non-stigmatising, replaces clinical labels with something everyone can understand and relate to.
- Hybrid Data Fusion: Passive wearable sensing meets active self-reporting, creating a richer picture of wellbeing than either alone.
- Clinical Pathway Integration: Designed from day one to fit into existing clinical pathways, not to replace them. The clinician dashboard and patient app work as a connected ecosystem.
Photo by Marc Rath, UWE Bristol Media Relations
About the Researcher
I'm Luigi Andrea Moretti, medical doctor (MD), former healthtech founder, and PhD candidate at UWE Bristol. I blend clinical insight, product thinking, and research rigour to build technology that clinicians actually adopt and patients genuinely use.
MEMoPAD is my PhD research project. Before this, I co-founded other healthtech projects, including IntelliHearts, a wearable ECG system with emotion recognition.
Alignment with UK Health Priorities
The MEMoPAD project directly supports the UK's 10-Year Health Plan by developing the framework needed to integrate wearable devices and AI into clinical pathways. By empowering patients with their own data, we enable a more personalized approach to care. This focus on prevention addresses a key challenge identified by our co-design participants: supporting individuals in seeking help for the first time. By improving emotional wellbeing and supporting timely help-seeking, MEMoPAD contributes to the wider societal goal of prevention-first healthcare.
Cite or link to MEMoPAD
Writing about the project? Please call it MEMoPAD (Multimodal Emotion Monitoring in Clinical Pathways for Anxiety Disorders), a UWE Bristol PhD project, and link to memopad.luigiandreamoretti.com.
HTML link
<a href="https://memopad.luigiandreamoretti.com/">MEMoPAD (Multimodal Emotion Monitoring in Clinical Pathways for Anxiety Disorders)</a>To cite the MEMoPAD system
Moretti, L. A., Thompson, M., Matthews, P., Loizou, M., & Western, D. (2026). MEMoPAD: Multimodal Emotion Monitoring in Clinical Pathways for Anxiety Disorders. In Proceedings of the 2026 ACM Interactive Health Conference (pp. 1–4). ACM. https://doi.org/10.1145/3786579.3804994
BibTeX
@inproceedings{moretti2026memopad,
title = {{MEMoPAD}: Multimodal Emotion Monitoring in Clinical Pathways for Anxiety Disorders},
author = {Moretti, Luigi Andrea and Thompson, Miles and Matthews, Paul and Loizou, Michael and Western, David},
booktitle = {Proceedings of the 2026 ACM Interactive Health Conference},
year = {2026},
pages = {1--4},
publisher = {ACM},
doi = {10.1145/3786579.3804994}
}To cite our review of affective computing in anxiety disorders
Moretti, L. A., Thompson, M., Matthews, P., Loizou, M., & Western, D. (2025). Affective Computing in Anxiety Disorders: A Rapid Literature Review of Emotion Recognition Applications. In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2025) - Volume 2: HEALTHINF (pp. 273–284). SCITEPRESS. https://doi.org/10.5220/0013322800003911
BibTeX
@inproceedings{moretti2025affective,
title = {Affective Computing in Anxiety Disorders: A Rapid Literature Review of Emotion Recognition Applications},
author = {Moretti, Luigi Andrea and Thompson, Miles and Matthews, Paul and Loizou, Michael and Western, David},
booktitle = {Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2025) - Volume 2: HEALTHINF},
year = {2025},
pages = {273--284},
publisher = {SCITEPRESS},
isbn = {978-989-758-731-3},
doi = {10.5220/0013322800003911}
}