Best practices and current implementation of emerging smartphone-based (bio)sensors Part 1: Data handling and ethics


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Document Outline

  • Best practices and current implementation of emerging smartphone-based (bio)sensors – Part 1: Data handling and ethics
    • 1. Introduction
    • 2. Acquisition & handling of data from smartphone-based (bio)sensors
      • 2.1. Analytical data formats
        • 2.1.1. Electrochemical data
        • 2.1.2. Optical data
        • 2.1.3. Metadata
      • 2.2. Conditions during data acquisition
      • 2.3. Smartphone app interfaces for data collection
      • 2.4. Data processing
        • 2.4.1. Color space transformation
        • 2.4.2. Normalization and noise removal
        • 2.4.3. Segmentation
      • 2.5. Data interpretation and artificial intelligence
        • 2.5.1. AI for feature selection
        • 2.5.2. AI in result interpretation (regression)
        • 2.5.3. Conventional and federated ML
      • 2.6. Online and offline data handling
    • 3. Privacy and security of data handling by smartphone-based (Bio)sensors
      • 3.1. Privacy and personal data protection: an EU framework
      • 3.2. Data handling for smartphone-based (bio)sensors
        • 3.2.1. Consent
      • 3.3. Privacy
      • 3.4. Data security and authentication
      • 3.5. Data transfer
        • 3.5.1. Online wireless data transfer
        • 3.5.2. Offline wireless data transfer
      • 3.6. Data storage
        • 3.6.1. Data storage for corporations
      • 3.7. Big data: fair (meta)data collection
    • 4. Case study: near real-time dynamic data handling for mapping of infectious disease
    • 5. Perspectives & proposed best practices for the development of emerging smartphone based (bio)sensors
    • Author contributions
    • Funding statements
    • Declaration of competing interest
    • Data availability
    • ABBREVIATIONS
    • Appendix A. Supplementary data
    • References

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