How can you creatively improve the accuracy of wearable sensors?

1 Use Machine Learning

Machine learning is a branch of artificial intelligence that can learn from data and make predictions or decisions. Machine learning can help improve the accuracy of wearable sensors by analyzing the raw signals and extracting meaningful features, such as patterns, trends, or anomalies. Machine learning can also help reduce noise, filter out artifacts, and calibrate the sensors. For example, machine learning can help detect and correct motion artifacts that can affect the accuracy of heart rate or blood pressure measurements from wearable sensors.

2 Incorporate Contextual Information

Contextual information is the information that describes the situation or environment of the user or the sensor. Contextual information can help improve the accuracy of wearable sensors by providing additional clues or feedback that can enhance or validate the sensor data. Contextual information can include factors such as location, activity, mood, time, weather, or social interactions. For example, contextual information can help adjust the sensor data based on the user's activity level, such as resting, walking, running, or cycling.

3 Combine Multiple Sensors

Multiple sensors can help improve the accuracy of wearable sensors by providing complementary or redundant data that can increase the confidence or resolution of the measurements. Multiple sensors can be integrated into a single device or distributed across different locations on the body. Multiple sensors can also measure different types of signals, such as electrical, optical, mechanical, or chemical. For example, multiple sensors can help measure blood pressure more accurately by combining the data from an optical sensor that measures pulse wave velocity and an electrical sensor that measures electrocardiogram.

4 Optimize Sensor Placement

Sensor placement is the position or location of the sensor on the body. Sensor placement can affect the accuracy of wearable sensors by influencing the quality and quantity of the signal that the sensor can capture. Sensor placement can also affect the comfort and convenience of the user. Sensor placement should be optimized based on the type and purpose of the sensor, the anatomy and physiology of the body, and the preferences and behavior of the user. For example, sensor placement can help improve the accuracy of temperature measurements by choosing a site that is close to the core body temperature, such as the ear or the forehead.

5 Involve User Feedback

User feedback is the information that the user provides to the sensor or the system based on their experience or perception. User feedback can help improve the accuracy of wearable sensors by allowing the user to verify, correct, or supplement the sensor data. User feedback can also help improve the user satisfaction and engagement with the sensor or the system. User feedback can be collected through various methods, such as surveys, ratings, comments, or gestures. For example, user feedback can help improve the accuracy of mood measurements by asking the user to rate their emotional state on a scale or to select an emoji that matches their mood.

6 Experiment with Novel Materials

Novel materials are materials that have unique or enhanced properties that can improve the performance or functionality of the sensor. Novel materials can help improve the accuracy of wearable sensors by enabling new or better ways of sensing, transmitting, or processing the signals. Novel materials can also help improve the durability, flexibility, or biocompatibility of the sensor. Novel materials can include materials such as nanomaterials, smart textiles, or biodegradable polymers. For example, novel materials can help improve the accuracy of oxygen saturation measurements by using nanomaterials that can change color or fluorescence in response to oxygen levels.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?