TIDUDO6B May   2019  – October 2020

 

  1.   Description
  2.   Resources
  3.   Features
  4.   Applications
  5.   5
  6. 1System Description
    1. 1.1 Introduction to Parameters Measured Using TIDA-01580
    2. 1.2 High-Level System Description
    3. 1.3 Typical Applications
    4. 1.4 System Specifications and Design Features
    5. 1.5 Key System Specifications
  7. 2System Overview
    1. 2.1 Block Diagram
    2. 2.2 Highlighted Products
      1. 2.2.1 AFE4900
      2. 2.2.2 CC2640R2F
      3. 2.2.3 TPS61099
      4. 2.2.4 TPS63036
      5. 2.2.5 TPD1E10B06
    3. 2.3 System Design Theory and Design Considerations
      1. 2.3.1  AFE4900 and Power Supply
      2. 2.3.2  CC2640R2F Microcontroller
      3. 2.3.3  PPG Measurement
      4. 2.3.4  ECG Measurement
        1. 2.3.4.1 Two-Electrode Configuration
        2. 2.3.4.2 Three-Electrode Configuration
      5. 2.3.5  Selecting TX Supply (TX_SUP) Value for Driving LEDs
      6. 2.3.6  Generating TX Supply for Driving LEDs
        1. 2.3.6.1 Programming Output Voltage
        2. 2.3.6.2 Maximum Output Current
        3. 2.3.6.3 Input and Output Capacitor Selection
        4. 2.3.6.4 Switching Frequency
        5. 2.3.6.5 WEBENCH® Simulation for TPS61099 Boost Converter
      7. 2.3.7  Generating RX Supply for AFE4900
        1. 2.3.7.1 Setting Output Voltage
        2. 2.3.7.2 Capacitor Selection
        3. 2.3.7.3 Output Current Limit
        4. 2.3.7.4 Inductor Selection
        5. 2.3.7.5 TINA-TI™ Simulation for TPS63036
      8. 2.3.8  Generating I/O Supply
      9. 2.3.9  Battery Input and Reservoir Capacitors
      10. 2.3.10 Battery Life Calculations
        1. 2.3.10.1 AFE4900 Current Consumption
        2. 2.3.10.2 CC2640R2F Current Consumption
        3. 2.3.10.3 On-State Current Calculations
        4. 2.3.10.4 Off-State Current Calculations (Considering Battery Voltage = 3 V)
      11. 2.3.11 External Memory
      12. 2.3.12 LED Indications
      13. 2.3.13 Connections Between Sensor Board and ECG Board
  8. 3Hardware, Software, Testing Requirements, and Test Results
    1. 3.1 Required Hardware and Software
      1. 3.1.1 Hardware
        1. 3.1.1.1 Connecting Optical Sensor and ECG Boards to Main Board
        2. 3.1.1.2 Difference Between PPG Sensor Boards
      2. 3.1.2 Software
        1. 3.1.2.1 Software Loading for TIDA-01580 Board (Transmit Side of BLE)
        2. 3.1.2.2 LabVIEW™ File Execution for Checking Measurement Data (Receive Side of BLE)
    2. 3.2 Testing and Results
      1. 3.2.1 Test Setup
      2. 3.2.2 Test Results
        1. 3.2.2.1 Heart-Rate Measurement Using PPG (Green LED) and ECG
        2. 3.2.2.2 SpO2 Measurement Using Red and IR LEDs
        3. 3.2.2.3 PTT Measurement
        4. 3.2.2.4 Lead-Off Detect
          1. 3.2.2.4.1 AC Lead-Off Detect
          2. 3.2.2.4.2 DC Lead-Off Detect
        5. 3.2.2.5 Low-Battery Indication
        6. 3.2.2.6 Waveforms for DC/DC Converters
        7. 3.2.2.7 Battery Life Test
  9. 4Design Files
    1. 4.1 Schematics
    2. 4.2 Bill of Materials
    3. 4.3 PCB Layout Recommendations
      1. 4.3.1  Layout for Main Board
      2. 4.3.2  Connection From PDs to AFE
      3. 4.3.3  Connections From LEDs to AFE
      4. 4.3.4  Connections From ECG PADs to AFE
      5. 4.3.5  Connections Between BT and AFE
      6. 4.3.6  Connections Between BT Antenna and Chip
      7. 4.3.7  Boost Converter
      8. 4.3.8  Buck-Boost Converter
      9. 4.3.9  Layouts for PPG Sensor Boards
      10. 4.3.10 Layout for ECG Sensor Board
      11. 4.3.11 Layout Prints
    4. 4.4 Altium Project
    5. 4.5 Gerber Files
    6. 4.6 Assembly Drawings
  10. 5Software Files
  11. 6Related Documentation
    1. 6.1 Trademarks
  12. 7About the Authors
  13.   Revision History

3.2.2.3 PTT Measurement

Figure 3-28 shows the PTT measurement.

GUID-9E387424-B3B7-41A6-9631-38987DEC1E54-low.pngFigure 3-28 Measurement Showing Constant PTT
Note:

During testing, it was observed that the power line noise and other motion artifacts getting coupled to the PPG signals drastically reduced the SNR. For HRM applications, it is imperative to remove the noise and baseline drift. Heart-rate estimation usually requires an algorithm that filters the noise and detects the beat-to-beat heart rate and average heart rate. Even under rest conditions, extraction of heart rate data can get complicated, due to sudden changes in the DC level of the signal, due to respiration and motion artifacts. The heart rate can be calculated by measuring the separation between the successive peaks of the signal after eliminating the effect of the sudden DC-level shifts. In the presence of artifacts such as motion, the PPG signal can be buried. This occurrence requires motion cancellation algorithms, usually aided by data from accelerometers, to be able to remove the motion artifact and extract the heart rate.