michael beigl

Prof. Dr. Michael Beigl

Research within KITHealthTech

Speeding up Digital Health

  • Research in High Performance Data Centers, and AI driven Software Dev for Health
  • Data Processing & Software for Digital Health
  • Processing Speed: High Performance Datastores for Health and Human Activity Data (defrost with FhG) and Trusted Data Stores (e.g. TreuMoDa with FIZ & SCC)
  • Development Speed / Adaptation: No/LoCode Framework for developing AI components for Activity and Health Data (edge-ML.org) and Certification & Auditing of AI-based health algorithms (VALIDATOR)
  • Usage Speed: (Automation of) Usability of Health Software (HIDDS4Health / DKFZ, AskUI Startup)

Artificial Intelligence (1) : Speeding Up Development

  • Edge-ML: Leading Open Source Framework for Lo/No-Code development with Lo/No-Code Approach (Edge-ML), assembles below methods
  • Leading AI / ML based Recognition Methods for detecting Health Conditions
  • General Health, Activities, Specific Dispositions
  • Psychological Diagnosis

Specific Topics:

  • Explainable AI Methods
  • Extending Cognitive Capabilities
  • Treatment Proposals using AI

Big Data Processing (9): Speeding up Processing & Validation of Health Data

  • Speeding up computing & storage: Smart Data Processing Systems, Mixed CPU/GPU Cluster Architectures, multi-level storage systems, integrated into simple accessible notebook tools
  • Speeding up Validation: Frameworks for AI Validation and Certification (VALIDATOR)
  • Speeding up use: legal and curation template processes

Digitalizing Health (10): Speeding up application of medical treatment by  

  • Digitalizing People: Expert Systems with ML-Learned AI to extend knowledge and skills of doctors, health personal, patients 
  • Digitalizing Processes: Cloud-based methods for health data processing User Interfaces for digital medical processes

Everytime Health using Ubiquitous Computing

  • Data Analytics (KI), Wearable Computing, HCI for Health

Research & Development of …

  • Wearable and Mobile Sensors & Apps
  • AI-driven sensors & systems for medical diagnosis (AURA, Earables)
  • Wearable Systems for staying healthy: AI-Physio Trainer, Bruxism Detector, Back/Neck pain Preventer (all through Earphones++, together with Bosch)
  • Medical Treatment support: Infected Wound Measurement and Recognizer, (together with Deutscher Wundrat)
  • Medical Treatment: hapticSleep : Fall into sleep within minutes; hapticActuator
  • Human Activity Recognition Algorithms and Datasets using Smartphones and Earables for various health applications

Intelligent Wearables (8) 

  • Wearables for Everytime Health: From fundamental technology to usable devices
  • Embedded Devices (e.g. OpenEarable Platform)
  • Printable Devices (e.g. Tatoo stress)
  • Novel Sensors (e.g. AURA)
  • Novel Actuators (e.g. Exoskeletons,Tactile Displays for Sensory Replacement)

myHealth and communication (12)

  • Usable health using Smartphones
  • Mobile Apps for Health 
  • Frameworks to generate versions of mobile Apps for specific indications on NoCode basis