Top Techniques for Designing Power Optimized Medical Wearables

The medical healthcare sector is notorious for its disjointed and intricate system, making it a slow adopter of new technologies. However, the delivery of connected care solutions in the medical healthcare industry is about to undergo a transformation in the current era of smart and connected devices. According to research, by 2025, IoT healthcare spending will reach almost $1 trillion annually. By 2025, there will be between 25 and 50 billion connected devices, with a significant portion going toward healthcare. The Internet of Things (IoT) has made health monitoring possible around-the-clock, seven days a week. New technology has the potential to significantly enhance patient outcomes, reduce costs, and facilitate ease of use. 

 

The primary obstacle facing the designer is reconciling the opposing demands of performance and power. For medical wearable designs, low power solutions and optimized power management become essential. This article outlines the common power sources used by medical wearables, as well as power-optimized design and implementation strategies.  
 

• Common Ways Medical Wearable Devices Draw Power: 

A collection of subsystems that handle data collection, telemetry, analysis, and alerting make up a medical wearable system. The following are some typical scenarios/methods by which medical wearables obtain power:  
 

1. Sensor data must be sampled regularly or continuously in order to track a patient's movements or organs. 

2. It is necessary to transmit data to mobile applications or the cloud once or twice a day, depending on one's health. greater power  

3. When there is an alert, sending data to the monitoring facility quickly and frequently uses a lot of energy. 

4. Healthcare wearable devices enter search mode for a predetermined amount of time when they are not connected to a Wi-Fi network or are not using a mobile device with Bluetooth. At this time, the device uses more energy.  

5. More power is needed to analyze the complex algorithm, which typically takes longer to run, in order to analyze the patient's body sensor data.  

 

• Prioritize the Functionalities in the Case of Low Power Condition: 

When battery-operated medical wear is used continuously and there isn't a convenient place to charge it, the battery capacity may drop below a certain point, forcing the device to run in low power mode. However, there are still some crucial core functions that must be carried out promptly in order to monitor a patient's vital changes or alert situations. The power management strategy for wearables must permit the use of more power for these essential functions. Here are a few instances of this kind:  

 

1. Even in low power mode, wearables that monitor patients' cough, breathing, and wheezing patterns in order to determine their asthmatic severity must continuously record and analyze audio.  

2. When an unusual circumstance or alert condition arises, data must be promptly reported to a remote medical facility.  

3. The user will receive notification through a display device or vibrator of the abnormal health condition.  

4. Before the battery runs out entirely, abnormal health condition data needs to be stored in non-volatile memory in the event that connectivity with a monitoring device (cloud/mobile application) is lost. These details might be necessary for additional situational analysis.  

 

Architecture and Hardware Selection for Power Optimized Medical Wearable: 

Manufacturers are providing System-on-Chip (SoC) solutions with a combination of a power-efficient microcontroller and application processor for complex data analysis/algorithm to help designers overcome the engineering challenges associated with medical wearables. Additionally, one may choose to interface the two independently using a communication bus (I2C, UART, SPI, etc.). The low power controller should be connected to peripherals needed for ongoing patient health monitoring, such as wearable health monitoring devices and sensors affixed to the patient's body, such as fuel gauges for battery monitoring.  

 

 

Hardware platform and component selection also play an important role for power-optimized medical wearable product design. Here are few points to be considered: 

1. Select SoCs, RAM, EEPROMs, and connectivity peripherals (Wi-Fi, LTE, Bluetooth), among others, that have low power consumption and low operating mode support. Before choosing, review the datasheet and the power requirements.  

2. Measure the actual power consumption with an off-the-shelf platform if at all possible.  

3. Medical equipment that travels with a patient must be made with the possibility of being handled roughly and subjected to high and low temperatures and moisture levels in mind.  

4. Determine how much memory will be needed to hold the patient's medical records. Select memory that uses less power.  

 

• Design & Implementation Techniques for Power Optimized Wearable: 

1. Unnecessary software services that aren't needed for device operation should be disabled or removed.  

2. Most of the time, keep your highly power-hungry processor in low power mode. Utilize an ultra-low power controller to continuously record data and activate the advanced processor when needed.  

3. The majority of new smartphones come pre-installed with Bluetooth® Smart, or Bluetooth Low Energy, which makes it the industry standard for wearable wireless communication.  

4. Separate the algorithm for complex analysis into two stages. The first step would be to analyze the possibility of an abnormal condition using a simple algorithm that runs on a low power controller. To verify the anomalous circumstance, a sophisticated algorithm executing on a high-end processor would be the next step. 

5. Reduce the frequency of data transmission to the remote monitoring facility if your health is normal.  

6. Don't let the network scan timeout period last too long.  

7. When the device is operating in low power mode, disable non-critical functions. for example, calibrating, self-testing, updating firmware, etc.  

8. Turn off unused peripheral clocks in the SoC.  

9. Determine the best data frame format to minimize the amount of data transmitted from a wearable device to a mobile app or cloud server.  

10. To maintain the advanced processor in sleep mode for the majority of the device's operation, various actuators (such as vibrators, LEDs, or displays) that are used to alert patients about abnormal situations should, if at all possible, be connected to a continuous ON ultra-low power mode controller.  

 

Conclusion: 

Although in the coming era of mobile health and IoT in healthcare, there will be pivotal components including highly sensitive biosensors, low-power integrated electronic circuits, low-power and reliable wireless communication, and obviously a sufficient power source. As the recent advances in nanotechnology and materials have enabled the realization of smaller and more sensitive sensors consuming less energy as well as low-power and smaller sized electronics, the increasing dependence on communication and interaction with other devices and a mobile cloud requires much higher power to operate the new-generation devices. 

While designing medical product, reliability, accuracy, and safety are important areas to keep in mind. But when we transform such medical product into the wearable segment, its battery life also becomes a very important factor to be taken into consideration. A similar solution has been created in a recent case study of Silicon Signals, where the customer has developed an algorithm to detect asthma and Silicon Signals has developed an end-to-end solution (including hardware, firmware, mobile application, cloud database and web application) and integrated customer’s asthma detection algorithm in it.