Category: Digital Twin
Industry Research Hub — AL360° Compliance
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Research Hub — Healthcare Compliance Healthcare AI sits at the nexus of privacy, safety and patient rights. In the EU, the Artificial Intelligence Act classifies AI systems used as safety components of medical devices as high‑risk. Article 6(1)(b) specifies that an AI system is high‑risk if it serves as a…
End-to-End Prototype using AffectLog’s Privacy-Preserving Mental Health Digital Twin Platform
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Introduction Integrating personal health data with clinical records can greatly improve the prediction and management of mental health conditions. In this prototype, we design a privacy-preserving mental health digital twin platform that unifies data from iPhone sensors, doctor’s notes, and electronic health records (EHR) to create a dynamic digital representation…
PersonaCore: A Federated Neuromorphic Edge AI Platform for Privacy-Preserving Affective Digital Twins
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Abstract Affective Digital Twins (ADT) are virtual replicas of human emotional and cognitive states, enabling simulation and personalized AI interactions in human-centric applications. This paper presents AffectLog PersonaCore, a technical framework for implementing ADTs via a federated, privacy-preserving, neuromorphic computing platform. We detail how PersonaCore innovates on-device federated neuromorphic processing…
Affective Digital Twin: Advancements and Future Directions
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Affective Digital Twin Concept Affective Digital Twin (ADT) refers to a digital replica of an individual that encapsulates not only their physical state but also their cognitive and emotional characteristics. It builds upon affective computing (which enables machines to recognize and simulate human emotions) and digital twin technology (virtual models…
