A Wearable Wrist Band-Type System for Multimodal Biometrics Integrated with Multispectral Skin Photomatrix and Electrocardiogram Sensors

Abstract

Multimodal biometrics are promising for providing a strong security level for personal authentication, yet the implementation of a multimodal biometric system for practical usage need to meet such criteria that multimodal biometric signals should be easy to acquire but not easily compromised. We developed a wearable wrist band integrated with multispectral skin photomatrix (MSP) and electrocardiogram (ECG) sensors to improve the issues of collectability, performance and circumvention of multimodal biometric authentication. The band was designed to ensure collectability by sensing both MSP and ECG easily and to achieve high authentication performance with low computation, efficient memory usage, and relatively fast response. Acquisition of MSP and ECG using contact-based sensors could also prevent remote access to personal data. Personal authentication with multimodal biometrics using the integrated wearable wrist band was evaluated in 150 subjects and resulted in 0.2% equal error rate ( EER ) and 100% detection probability at 1% FAR (false acceptance rate) ( PD . 1 ), which is comparable to other state-of-the-art multimodal biometrics. An additional investigation with a separate MSP sensor, which enhanced contact with the skin, along with ECG reached 0.1% EER and 100% PD . 1 , showing a great potential of our in-house wearable band for practical applications. The results of this study demonstrate that our newly developed wearable wrist band may provide a reliable and easy-to-use multimodal biometric solution for personal authentication.

Keywords: ECG; integrated wearable device; majority voting; multimodal biometrics; multispectral skin photomatrix.

Figure 1

Illustrations of differences in penetration depth for Multispectral Skin Photomatrix (MSP) sensors by various wavelengths and distances between light source and detector.

Figure 2

An Electrocardiogram (ECG) pulse measured by our in-house integrated wearable band with annotations for P-QRS complex-T.

Figure 3

A block diagram of our in-house wearable security band (WSB).

Figure 4

A block diagram of ECG signal processing module.

Figure 5

A block diagram of MSP acquisition module.

Figure 6

(A) The layout of LED arrays in an MSP module; (B) an MSP module equipped with eight red light LEDs and eight infrared light LEDs; and (C) an MSP module equipped with eight yellow LEDs and eight infrared LEDs. For both designs, 32 photodiodes (PD) are arranged between two layers of LEDs in a 2 × 16 matrix form.

Figure 7

The operating process of the LED sources and Photodiode (PD) detectors for the single cycle of the MSP data acquisition. One of the 16 LEDs at the first visual channel (V1) begins to turn on and each of the 32 PDs detects optical signals in sequence. Then, after an interval, the next LED at the second visual LED channel (V2) turns on and the PDs detect the signals. This process is repeated for each of eight visual LEDs (V1-V8) and eight infrared LEDs (IR1-IR8). The entire process spans approximately 1 s.

Figure 8

The optimized wrist surface type band by firmly attaching the PD array onto the wrist (Left panel). An examples of two bands with different curvatures optimized for: participants with small wrist (left in the right panel) and participants with normal or thick wrists (right in the right panel).

Figure 9

An effect of the application of a user template guided filter for MSP signal. The blue line shows the user template which is enrolled in the device. The black line represents the test signal, and the red line is guided filtering result with using template as a guide image.

Figure 10

A comparison of the histograms of distance values before (left) and after (right) the normalization by the maximum distance. A distance value refers to an Euclidean distance between a user template and a tested biometric signal (ECG or MSP) of the genuine user or an imposter.

Figure 11

Snapshots of our in-house data acquisitions for ECG (A,B) and MSP (C). One wearable ECG sensor contacts the wrist of the left arm (A) and a subject must touch ECG sensors with their index finger of the right hand to acquire ECG data to measure the potential difference between left wrist and right finger (B). MSP sensor array is placed on the right wrist to measure the data (C).

Figure 12

False Acceptance Rate ($\mathrm{FAR}$) and False Rejection Rate ($\mathrm{FRR}$) graphs for different threshold values for proposed multimodal biometrics methods: ECG + MSP integrated in Wearable Security Band (WSB); and ECG and MSP separately measured for better contact (ECG + separate MSP sensor), respectively.