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Potential of Augmented Reality and Virtual Reality Technologies to Promote Wellbeing in Older Adults
Open AccessArticle

Deep-cARe: Projection-Based Home Care Augmented Reality System with Deep Learning for Elderly

1
Media System Lab, Yonsei University, Seodaemun-gu, Seoul 03722, Korea
2
College of Computer Science & Software, Chung-Ang University, Dongjak-gu, Seoul 06911, Korea
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(18), 3897; https://doi.org/10.3390/app9183897
Received: 27 June 2019 / Revised: 6 September 2019 / Accepted: 7 September 2019 / Published: 17 September 2019
(This article belongs to the Special Issue Augmented Reality: Current Trends, Challenges and Prospects)
Developing innovative and pervasive smart technologies that provide medical support and improve the welfare of the elderly has become increasingly important as populations age. Elderly people frequently experience incidents of discomfort in their daily lives, including the deterioration of cognitive and memory abilities. To provide auxiliary functions and ensure the safety of the elderly in daily living situations, we propose a projection-based augmented reality (PAR) system equipped with a deep-learning module. In this study, we propose three-dimensional space reconstruction of a pervasive PAR space for the elderly. In addition, we propose the application of a deep-learning module to lay the foundation for contextual awareness. Performance experiments were conducted for grafting the deep-learning framework (pose estimation, face recognition, and object detection) onto the PAR technology through the proposed hardware for verification of execution possibility, real-time execution, and applicability. The precision of the face pose is particularly high by pose estimation; it is used to determine an abnormal user state. For face recognition results of whole class, the average detection rate (DR) was 74.84% and the precision was 78.72%. However, for face occlusions, the average DR was 46.83%. It was confirmed that the face recognition can be performed properly if the face occlusion situation is not frequent. By object detection experiment results, the DR increased as the distance from the system decreased for a small object. For a large object, the miss rate increased when the distance between the object and the system decreased. Scenarios for supporting the elderly, who experience degradation in movement and cognitive functions, were designed and realized, constructed using the proposed platform. In addition, several user interfaces (UI) were implemented according to the scenarios regardless of distance between users and the proposed system. In this study, we developed a bidirectional PAR system that provides the relevant information by understanding the user environment and action intentions instead of a unidirectional PAR system for simple information provision. We present a discussion of the possibility of care systems for the elderly through the fusion of PAR and deep-learning frameworks. View Full-Text
Keywords: Projection Augmented Reality; elderly; home care; assistance; safety; deep learning; pose estimation; face recognition; object detection Projection Augmented Reality; elderly; home care; assistance; safety; deep learning; pose estimation; face recognition; object detection
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Park, Y.J.; Ro, H.; Lee, N.K.; Han, T.-D. Deep-cARe: Projection-Based Home Care Augmented Reality System with Deep Learning for Elderly. Appl. Sci. 2019, 9, 3897.

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