Lifelog retrieval for memory stimulation of people with memory impairment

Oliveira, Gabriel de; Bolaños, Marc; Talavera, Estefanía; Gelonch, Olga; Garolera, Maite; Radeva, Petia

doi:10.1016/b978-0-12-814601-9.00016-x

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…This study is very promising because it achieves results that are as accurate as those of other methods in the literature. Oliveira-Barra et al [ 43 ] proposed a comprehensive methodology for egocentric photo stream analysis. They performed a summary of autobiographical episodes and a semantic key-frame selection and, finally, implemented text-based inverted index retrieval techniques.…”

Section: Resultsmentioning

confidence: 99%

Lifelog Retrieval From Daily Digital Data: Narrative Review

Ribeiro

Trifan

Neves

2022

JMIR Mhealth Uhealth

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Background Over the past decade, the wide availability and small size of different types of sensors, together with the decrease in pricing, have allowed the acquisition of a substantial amount of data about a person’s life in real time. These sensors can be incorporated into personal electronic devices available at a reasonable cost, such as smartphones and small wearable devices. They allow the acquisition of images, audio, location, physical activity, and physiological signals among other data. With these data, usually denoted as lifelog data, we can then analyze and understand personal experiences and behaviors. This process is called lifelogging. Objective The objective of this paper was to present a narrative review of the existing literature about lifelogging over the past decade. To achieve this goal, we analyzed lifelogging applications used to retrieve relevant information from daily digital data, some of them with the purpose of monitoring and assisting people with memory issues and others designed for memory augmentation. We aimed for this review to be used by researchers to obtain a broad idea of the type of data used, methodologies, and applications available in this research field. Methods We followed a narrative review methodology to conduct a comprehensive search for relevant publications in Google Scholar and Scopus databases using lifelog topic–related keywords. A total of 411 publications were retrieved and screened. Of these 411 publications, 114 (27.7%) publications were fully reviewed. In addition, 30 publications were manually included based on our bibliographical knowledge of this research field. Results From the 144 reviewed publications, a total of 113 (78.5%) were selected and included in this narrative review based on content analysis. The findings of this narrative review suggest that lifelogs are prone to become powerful tools to retrieve memories or increase knowledge about an individual’s experiences or behaviors. Several computational tools are already available for a considerable range of applications. These tools use multimodal data of different natures, with visual lifelogs being one of the most used and rich sources of information. Different approaches and algorithms to process these data are currently in use, as this review will unravel. Moreover, we identified several open questions and possible lines of investigation in lifelogging. Conclusions The use of personal lifelogs can be beneficial to improve the quality of our life, as they can serve as tools for memory augmentation or for providing support to people with memory issues. Through the acquisition and analysis of lifelog data, lifelogging systems can create digital memories that can be potentially used as surrogate memory. Through this narrative review, we understand that contextual information can be extracted from lifelogs, which provides an understanding of the daily life of a person based on events, experiences, and behaviors.

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Section: Resultsmentioning

confidence: 99%

Lifelog Retrieval From Daily Digital Data: Narrative Review

Ribeiro

Trifan

Neves

2022

JMIR Mhealth Uhealth

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“…Wearable cameras can play the role of a digital memory helping people with memory problems to improve the quality of their daily life (Oliveira-Barra et al, 2019). Thus, the recording, storage and retrieval of inaccessible memories through visual lifelogging has been extensively studied the last years (Silva et al, 2016).…”

Section: Background 21 Visual Lifeloggingmentioning

confidence: 99%

A First-person Database for Detecting Barriers for Pedestrians

Θεοδοσίου

Partaourides

Atun

et al. 2020

Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application

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Egocentric vision, which relates to the continuous interpretation of images captured by wearable cameras, is increasingly being utilized in several applications to enhance the quality of citizens' life, especially for those with visual or motion impairments. The development of sophisticated egocentric computer vision techniques requires automatic analysis of large databases of first-person point of view visual data collected through wearable devices. In this paper, we present our initial findings regarding the use of wearable cameras for enhancing the pedestrians' safety while walking in city sidewalks. For this purpose, we create a first-person database that entails annotations on common barriers that may put pedestrians in danger. Furthermore, we derive a framework for collecting visual lifelogging data and define 24 different categories of sidewalk barriers. Our dataset consists of 1796 annotated images covering 1969 instances of barriers. The analysis of the dataset by means of object classification algorithms, depict encouraging results for further study.

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“…A lifelog selection using semantic characteristics was presented in [24] which proposed a smart keyframe selection using summarization methods, people and semantically-rich scenes. The method is based on two parallel steps: (1) selection of keyframe using semantic segmentation and summarization of the whole day taking into account the common relationship of images, and (2) selection of image processes using the presence of faces and basic objects.…”

Section: Retrieval Systemsmentioning

confidence: 99%

“…The lifelogging retrieval can play significant role in the improvement of autobiographical memory assisting people with poor short-term memory recall capacity. Therefore, several applications can be developed to improve the well-being of people with memory impairments [24], such as Alzheimer and other dementias.…”

Section: Applicationsmentioning

confidence: 99%

Visual Lifelogs Retrieval: State of the Art and Future Challenges

Θεοδοσίου

Lanitis

2019

2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)

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The use of wearable cameras covers several areas of application nowadays, where the need for developing smart applications providing the sustainability and well-being of citizens it is more necessary than ever before. The tremendous amount of lifelogging data to extract valuable knowledge about the every day life of the wearers requires state of the art retrieval techniques to efficiently store, access, search and retrieve useful information. Several works have been proposed combining computer vision and machine learning techniques to analyze the content of the data captured from visual wearable devices on a daily basis. This paper presents an overview of the progress in visual lifelogging retrieval and indicates the current advances and future challenges, highlighting the prospects of incorporating visual lifelogging retrieval in social computing applications.

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Lifelog retrieval for memory stimulation of people with memory impairment

Cited by 7 publications

References 8 publications

Lifelog Retrieval From Daily Digital Data: Narrative Review

Lifelog Retrieval From Daily Digital Data: Narrative Review

A First-person Database for Detecting Barriers for Pedestrians

Visual Lifelogs Retrieval: State of the Art and Future Challenges

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