Recent Advances in Nanomaterial-Based Biosignal Sensors

Area of Science:

• Materials Science
• Biomedical Engineering
• Electronics

Background:

• Biosignal sensors are crucial for evaluating user well-being, predicting behavior, and aiding disease diagnosis in medical fields, robotics, and wearable electronics.
• Nanomaterials enhance biosignal sensor adaptability due to their stretchability, high surface-to-volume ratio, and tunable properties, enabling direct body placement for signal acquisition.

Purpose of the Study:

• To categorize and analyze nanomaterial-based biosignal sensors.
• To discuss current limitations and potential improvements in nanomaterial-based biosignal sensor technology.
• To highlight the role of deep learning and human-machine interfaces in advancing biosignal sensor applications.

Main Methods:

• Categorization of nanomaterial-based biosignal sensors into three types: biophysical, bioelectric, and biochemical.
• Analysis of the properties and applications of each sensor category.
• Review of limitations, improvements, and future directions, including signal processing and interface technologies.

Main Results:

• Nanomaterial-based biosignal sensors are classified into biophysical (detecting deformation), bioelectric (capturing electrical signals), and biochemical (analyzing biofluids).
• The review details the specific advantages and challenges associated with each sensor type.
• Emerging trends include deep learning for signal processing and enhanced human-machine interfaces.

Conclusions:

• Nanomaterial integration significantly advances biosignal sensor capabilities for diverse applications.
• Addressing current limitations is key to unlocking the full potential of these sensors.
• Future development should focus on integrating advanced signal processing and human-machine interfaces for improved functionality.