You’re asking how acoustic sensors work in wearable devices. They operate by converting sound into electrical signals for analysis. This process consists of three main stages: sound capture, electrical signal conversion, and signal processing.

1. Sound Capture:

• Microphone: The core of an acoustic sensor is the microphone. The microphone converts surrounding sound energy into vibration energy. The conversion method varies slightly depending on the type of microphone.
  • MEMS Microphone (Micro-Electro-Mechanical System Microphone): This is the most widely used microphone in wearable devices today. A tiny diaphragm vibrates in response to sound waves, causing a change in electrical capacitance, which is then converted into an electrical signal. It has advantages such as small size, low power consumption, and excellent performance.

2. Electrical Signal Conversion:

• The vibration energy converted by the microphone is converted into an electrical signal. This electrical signal is very weak and needs to be amplified.
• ADC (Analog-to-Digital Converter): The amplified analog signal is converted into a digital signal. Digital signals are easily processed by computers or processors.

3. Signal Processing:

• The sound data converted into a digital signal is processed in various ways by the wearable device’s processor.
  • Voice Recognition: Voice recognition algorithms convert the user’s voice into text or recognize specific voice commands.
  • Noise Cancellation: Works by analyzing the frequency of ambient noise and generating sound waves with the opposite phase to cancel out the noise.
  • Bioacoustic Analysis: Analyzes subtle sounds generated by the body, such as heart sounds and breathing sounds, to monitor health status.
  • Ambient Environment Analysis: Detects specific sounds (e.g., sirens, breaking glass) to provide notifications to the user.

Additional Factors:

• Directionality: Some wearable devices are equipped with multiple microphones to provide sound direction detection. This can be used to emphasize sounds from a specific direction or improve noise cancellation performance.
• Frequency Response: Microphones are designed to detect sounds in a specific frequency range well. Microphones with appropriate frequency response characteristics are used depending on the purpose of the wearable device.
• Sampling Rate: This is an indicator of how often a signal is sampled when converting an analog signal to a digital signal. A higher sampling rate allows obtaining a digital signal closer to the original sound, but it has the disadvantage of increasing data capacity.

Summary:

Acoustic sensors in wearable devices capture sound through a microphone, convert it into an electrical signal, and perform various functions through digital signal processing. Through this process, various services such as voice recognition, health monitoring, and environment recognition are provided, playing an important role in user convenience, safety, and health management. With the advancement of technology, as smaller and higher-performance acoustic sensors are developed, the range of applications for wearable devices is expected to expand further.

Excuse me, author! I was curious about how exactly the acoustic sensors used in wearables capture sound. How is it different from a simple microphone?

Ah, at its core, you can think of it as a MEMS microphone. A tiny diaphragm reacts to sound and converts it into an electrical signal. It doesn’t end there. By converting that signal into digital and processing it in a processor, it enables functions like voice recognition, noise cancellation, and heart and breathing sound analysis.

Oh, so it can even monitor health? You said the sensor can capture things like heartbeats.

That’s right! It can analyze even the most subtle sounds from the body, so it can be used to track heartbeats and breathing. Of course, the higher the sensor performance, the more precise the measurements.

But if sounds are mixed from multiple directions, won’t they be difficult to hear or cause errors?

That’s why wearables these days have multiple microphones to detect direction. This is used to emphasize sounds from a specific direction or to eliminate ambient noise. Furthermore, high sampling rates allow for digital conversion that’s nearly identical to the original sound.