Skeeper AI

  • Securing of clinical data for AI diagnosis
  • AI lung/heart sound classification algorithm
  • Disease classification AI
  • Skeeper Edge AI

1. Securing of clinical data for AI diagnosis

  • Application of 5-step clinical verification process to secure reliability of clinical data
  • Securing disease classification data with high reliability through prospective clinical research
  • Maintenance of no loss of the original sound for each stage of transmission

2. AI lung/heart sound classification algorithm

  • Determination of abnormalities in lung/heart sound and development of disease classification model
  • Collection of disease data by Normal/abnormal lung/heart sound
  • A lightweight deep learning model

3. Disease classification AI

  • Artificial intelligence learning based on reliable clinical data
  • Optimization of data preprocessing to improve the accuracy of AI diagnosis
  • The calculation of probability for each disease by classifying the stethoscope data as Multi-task CNN Model
  • Application of X-AI module → Presentation of the basis for judging the outcome of AI diagnosis (Improving reliability)

4. Skeeper AI

  • Skeeper Edge AI an AIoT-based stethoscope solution, strengthening the security of stethoscope medical data through the intergration of edge computing and on-device AI.
  • Edge AI technology plays the role of primary screening for cardiopulmonary health for both medical professionals and homecare(applied to Skeeper R1)
  • AP

  • Octa-core AP
    Embedded Edge AI Solutions

  • Mode Selection

  • Camera
    Stethoscope (Heart, Lung, Abdomen, and Others)
    Data Transmission

  • UI/UX

  • Measurement, AI Analysis,
    History, and Others

  • Storage

  • +30,000 Measure Data

  • Wireless Communication

  • Bluetooth, Wi-Fi