The body temperature sensor is a crucial device that measures the temperature of the human body, enabling various applications such as medical diagnosis, health monitoring, and COVID-19 prevention. These sensors can be embedded in wearable devices, like smartwatches and fitness trackers, to provide continuous and real-time monitoring of body temperature.
Understanding the Apple Watch Temperature Sensing Feature
The Apple Watch Series 8 and later, as well as all models of Apple Watch Ultra, are equipped with two temperature sensors that measure wrist temperature every five seconds while the user sleeps. These sensors are strategically placed on the back crystal, near the skin, and just under the display, which helps reduce bias from the outside environment and improve accuracy.
The temperature sensing feature on the Apple Watch utilizes advanced algorithms to provide an aggregate for each night, allowing users to view relative changes from their established baseline temperature in the Health app. It’s important to note that this feature is not intended for medical diagnosis, treatment, or any other medical purpose, and it is not a thermometer that can provide on-demand wrist temperature measurements.
The temperature sensing feature is designed for users who are at least 14 years old, and wrist temperature data can be impacted by various physiological, lifestyle, and environmental factors.
Fitbit’s Temperature Monitoring Capabilities
Fitbit also offers a temperature monitoring feature that enables users to track their temperature over time, helping them identify patterns and spot trends. Users can manage or turn off the connection in the Thermometer app and take a temperature measurement by following the instructions in the Fitbit app. The body temperature value is then saved to the user’s Fitbit account and can be viewed on a body temperature graph.
Body Temperature Monitoring for COVID-19 Prevention
In the context of COVID-19 prevention, body temperature monitoring plays a crucial role in the preliminary screening of the population for fever. Wearable devices equipped with inertial and temperature sensors can be used to apply human behavior recognition (HAR) techniques to body surface temperature detection, enabling accurate body temperature monitoring and adjustment.
The sensing system typically consists of an STM 32-based microcontroller, a 6-axis (accelerometer and gyroscope) sensor, and a temperature sensor. These components capture the original data from individual participants under different daily activity scenarios. The collected raw data are then pre-processed through signal standardization, data stacking, and resampling.
For HAR, various machine learning (ML) and deep learning (DL) algorithms are implemented to classify the activities. The research has found that the Random Forest (RF) algorithm is the best-performing classifier, with an accuracy of 88.78%, which is higher than the case of the absence of temperature data (<78%).
Interestingly, the experimental results also show that participants’ body surface temperature during dynamic activities was lower compared to sitting. This observation can be associated with the possible missing fever population due to temperature deviations in COVID-19 prevention.
Technical Specifications and Sensor Characteristics
Body temperature sensors used in wearable devices typically have the following technical specifications and characteristics:
Sensor Type: Thermistor, Thermocouple, or Resistance Temperature Detector (RTD)
Measurement Range: 32°F to 113°F (0°C to 45°C)
Accuracy: ±0.1°C to ±0.5°C
Resolution: 0.01°C to 0.1°C
Response Time: 1 to 30 seconds
Sampling Rate: 1 to 10 samples per second
Power Consumption: 1 to 10 mW
Size: 2 mm x 2 mm to 5 mm x 5 mm
Interface: I2C, SPI, or Analog
The choice of sensor type, measurement range, accuracy, and other specifications depends on the specific application and the requirements of the wearable device.
Sensor Placement and Calibration
The placement of the body temperature sensor is crucial for accurate measurements. In wearable devices, the sensor is typically placed on the wrist, as it is a convenient location and provides a good balance between accessibility and thermal coupling with the body.
Proper calibration of the body temperature sensor is essential to ensure accurate readings. This process involves comparing the sensor’s output with a reference thermometer or a known temperature source. Calibration can be performed by the manufacturer or by the user, depending on the device’s design and the user’s technical expertise.
Data Processing and Analysis
The raw data collected from the body temperature sensor undergoes various pre-processing steps, such as signal standardization, data stacking, and resampling, to prepare it for further analysis.
Machine learning and deep learning algorithms are then employed to classify the user’s activities and provide accurate body temperature monitoring, even during dynamic activities. The Random Forest (RF) algorithm has been found to be the best-performing classifier, with an accuracy of up to 88.78%.
Practical Applications and Considerations
Body temperature sensors in wearable devices have a wide range of practical applications, including:
- Medical Diagnosis: Monitoring body temperature can help detect fever, infections, and other health conditions.
- Health Monitoring: Tracking changes in body temperature can provide insights into the user’s overall health and well-being.
- COVID-19 Prevention: Body temperature monitoring can be used for preliminary screening of the population for fever, a common symptom of COVID-19.
When using body temperature sensors, it’s important to consider factors that can impact the accuracy of the measurements, such as environmental conditions, user’s physiology, and the sensor’s placement on the body.
Conclusion
Body temperature sensors are essential devices for health monitoring and COVID-19 prevention. They provide continuous and real-time monitoring of body temperature, enabling users to identify patterns and spot trends. Advanced algorithms, such as Random Forest, can classify activities and provide accurate body temperature monitoring, even during dynamic activities.
By understanding the technical specifications, sensor characteristics, and practical applications of body temperature sensors, users can leverage these devices to improve their health and well-being, as well as contribute to the ongoing efforts to combat the COVID-19 pandemic.
References:
- Apple Watch Series 8 and later and Apple Watch Ultra Wrist Temperature Sensing Feature. (2024-02-05). Retrieved from https://support.apple.com/en-us/HT213275
- Series 9 – How to get body temperature measurements? Is mine defective? (2023-10-23). Retrieved from https://www.reddit.com/r/AppleWatch/comments/17eynir/series_9_how_to_get_body_temperature_measurements/
- Body Temperature Monitoring for Regular COVID-19 Prevention Using Wearable Devices. (2021-11-12). Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8622194/
- How can Fitbit help me track my temperature? – Google Help. (n.d.). Retrieved from https://support.google.com/fitbit/answer/14237207?hl=en
- Tracking body temperature – Project Logs – Quantified Self Forum. (2020-03-27). Retrieved from https://forum.quantifiedself.com/t/tracking-body-temperature/7921
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