Inertial Sensor-Based Gait Recognition: A Review.

Area of Science:

• Biometrics
• Human-Computer Interaction
• Wearable Technology

Background:

• Microelectromechanical systems (MEMS) have enabled low-cost, user-friendly inertial sensors.
• Individual gait patterns can be analyzed as unique biometric identifiers.
• Smart devices with inertial sensors are ubiquitous, driving research in gait recognition.

Purpose of the Study:

• To systematically review the state-of-the-art in inertial sensor-based gait recognition.
• To assess the effectiveness of current approaches in various conditions.
• To highlight the potential of this technology for security applications.

Main Methods:

• Review of current literature on inertial sensor-based gait recognition.
• Analysis of approaches using data from single smart devices.
• Evaluation of performance in controlled and uncontrolled environments.

Main Results:

• Advanced inertial sensor-based gait recognition effectively identifies users in controlled settings.
• Significant progress has been made for realistic use in uncontrolled circumstances.
• Current methods demonstrate high accuracy with data from single devices.

Conclusions:

• Inertial sensor-based gait recognition is a rapidly advancing field with significant potential.
• The technology shows promise for widespread security applications.
• Further development is expected to enhance applicability in diverse, real-world scenarios.