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. 2023 Dec 19;24(1):24.
doi: 10.3390/s24010024.

A Hybrid Protection Scheme for the Gait Analysis in Early Dementia Recognition

Francesco Castro  1 , Donato Impedovo  1 , Giuseppe Pirlo  1
Affiliations

A Hybrid Protection Scheme for the Gait Analysis in Early Dementia Recognition

Francesco Castro et al. Sensors (Basel). .

Abstract

Human activity recognition (HAR) through gait analysis is a very promising research area for early detection of neurodegenerative diseases because gait abnormalities are typical symptoms of some neurodegenerative diseases, such as early dementia. While working with such biometric data, the performance parameters must be considered along with privacy and security issues. In other words, such biometric data should be processed under specific security and privacy requirements. This work proposes an innovative hybrid protection scheme combining a partially homomorphic encryption scheme and a cancelable biometric technique based on random projection to protect gait features, ensuring patient privacy according to ISO/IEC 24745. The proposed hybrid protection scheme has been implemented along a long short-term memory (LSTM) neural network to realize a secure early dementia diagnosis system. The proposed protection scheme is scalable and implementable with any type of neural network because it is independent of the network's architecture. The conducted experiments demonstrate that the proposed protection scheme enables a high trade-off between safety and performance. The accuracy degradation is at most 1.20% compared with the early dementia recognition system without the protection scheme. Moreover, security and computational analyses of the proposed scheme have been conducted and reported.

Keywords: cancelable biometric; gait analysis; homomorphic cryptography; neurodegenerative disease; random projection; security healthcare.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Overall model of an early dementia recognition system with the implementation of the proposed hybrid protection scheme.
Figure 2
Figure 2
Random projection approach.
Figure 3
Figure 3
LSTM model architecture.
Figure 4
Figure 4
Setup of the data collection process.
Figure 5
Figure 5
Video capture and preprocessing.
Figure 6
Figure 6
Benchmark of the system accuracy obtained with and without feature protection in the case of walking from left to right.
Figure 7
Figure 7
Benchmark of the system accuracy obtained with and without feature protection in the case of walking from right to left.
Figure 8
Figure 8
Benchmark of the system accuracy obtained with and without feature protection in the case of walking in both directions.
See this image and copyright information in PMC

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