38 research outputs found

    Can Privacy-Aware Lifelogs Alter Our Memories?

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    The abundance of automatically-triggered lifelogging cameras is a privacy threat to bystanders. Countering this by deleting photos limits relevant memory cues and the informative content of lifelogs. An alternative is to obfuscate bystanders, but it is not clear how this impacts the lifelogger's recall of memories. We report on a study in which we compare viewing 1) unaltered photos, 2) photos with blurred people, and 3) a subset of the photos after deleting private ones, on memory recall. Findings show that obfuscated content helps users recall a lot of content, but it also results in recalling less accurate details, which can sometimes mislead the user. Our work informs the design of privacy-aware lifelogging systems that maximizes recall and steers discussion about ubiquitous technologies that could alter human memories

    Impact of video summary viewing on episodic memory recall:design guidelines for video summarizations

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    Reviewing lifelogging data has been proposed as a useful tool to support human memory. However, the sheer volume of data (particularly images) that can be captured by modern lifelogging systems makes the selection and presentation of material for review a challenging task. We present the results of a five-week user study involving 16 participants and over 69,000 images that explores both individual requirements for video summaries and the differences in cognitive load, user experience, memory experience, and recall experience between review using video summarisations and non-summary review techniques. Our results can be used to inform the design of future lifelogging data summarisation systems for memory augmentation

    The role of context in human memory augmentation

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    Technology has always had a direct impact on what humans remember. In the era of smartphones and wearable devices, people easily capture on a daily basis information and videos, which can help them remember past experiences and attained knowledge, or simply evoke memories for reminiscing. The increasing use of such ubiquitous devices and technologies produces a sheer volume of pictures and videos that, in combination with additional contextual information, could potentially significantly improve one’s ability to recall a past experience and prior knowledge. Calendar entries, application use logs, social media posts, and activity logs comprise only a few examples of such potentially memory-supportive additional information. This work explores how such memory-supportive information can be collected, filtered, and eventually utilized, for generating memory cues, fragments of past experience or prior knowledge, purposed for triggering one’s memory recall. In this thesis, we showcase how we leverage modern ubiquitous technologies as a vessel for transferring established psychological methods from the lab into the real world, for significantly and measurably augmenting human memory recall in a diverse set of often challenging contexts. We combine experimental evidence garnered from numerous field and lab studies, with knowledge amassed from an extensive literature review, for substantially informing the design and development of future pervasive memory augmentation systems. Ultimately, this work contributes to the fundamental understanding of human memory and how today’s modern technologies can be actuated for augmenting it

    Designing and evaluating a user interface for continous embedded lifelogging based on physical context

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    PhD ThesisAn increase in both personal information and storage capacity has encouraged people to store and archive their life experience in multimedia formats. The usefulness of such large amounts of data will remain inadequate without the development of both retrieval techniques and interfaces that help people access and navigate their personal collections. The research described in this thesis investigates lifelogging technology from the perspective of the psychology of memory and human-computer interaction. The research described seeks to increase my understanding of what data can trigger memories and how I might use this insight to retrieve past life experiences in interfaces to lifelogging technology. The review of memory and previous research on lifelogging technology allows and support me to establish a clear understanding of how memory works and design novel and effective memory cues; whilst at the same time I critiqued existing lifelogging systems and approaches to retrieving memories of past actions and activities. In the initial experiments I evaluated the design and implementation of a prototype which exposed numerous problems both in the visualisation of data and usability. These findings informed the design of novel lifelogging prototype to facilitate retrieval. I assessed the second prototype and determined how an improved system supported access and retrieval of users’ past life experiences, in particular, how users group their data into events, how they interact with their data, and the classes of memories that it supported. In this doctoral thesis I found that visualizing the movements of users’ hands and bodies facilitated grouping activities into events when combined with the photos and other data captured at the same time. In addition, the movements of the user's hand and body and the movements of some objects can promote an activity recognition or support user detection and grouping of them into events. Furthermore, the ability to search for specific movements significantly reduced the amount of time that it took to retrieve data related to specific events. I revealed three major strategies that users followed to understand the combined data: skimming sequences, cross sensor jumping and continued scanning

    Providing effective memory retrieval cues through automatic structuring and augmentation of a lifelog of images

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    Lifelogging is an area of research which is concerned with the capture of many aspects of an individual's life digitally, and within this rapidly emerging field is the significant challenge of managing images passively captured by an individual of their daily life. Possible applications vary from helping those with neurodegenerative conditions recall events from memory, to the maintenance and augmentation of extensive image collections of a tourist's trips. However, a large lifelog of images can quickly amass, with an average of 700,000 images captured each year, using a device such as the SenseCam. We address the problem of managing this vast collection of personal images by investigating automatic techniques that: 1. Identify distinct events within a full day of lifelog images (which typically consists of 2,000 images) e.g. breakfast, working on PC, meeting, etc. 2. Find similar events to a given event in a person's lifelog e.g. "show me other events where I was in the park" 3. Determine those events that are more important or unusual to the user and also select a relevant keyframe image for visual display of an event e.g. a "meeting" is more interesting to review than "working on PC" 4. Augment the images from a wearable camera with higher quality images from external "Web 2.0" sources e.g. find me pictures taken by others of the U2 concert in Croke Park In this dissertation we discuss novel techniques to realise each of these facets and how effective they are. The significance of this work is not only of benefit to the lifelogging community, but also to cognitive psychology researchers studying the potential benefits of lifelogging devices to those with neurodegenerative diseases

    Case studies in therapeutic SenseCam use aimed at identity maintenance in early stage dementia

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    In the absence of a medical cure for memory loss new technologies specialised in pervasive imaging are being incorporated into interventions for dementia. The practice of lifelogging is a digital capture of life experiences typically through mobile devices such as SenseCam. The lightweight wearable digital camera passively captures about 3,000 images a day. Lifelogging results in personal, recent prompts, potentially encouraging sharing of personal memories. This research investigated the incorporation of lifelogging technology into a therapeutic approach aimed to support people with dementia by using the Case Study method, an exploratory and descriptive approach. The case study is a method of empirical inquiry that enables investigation of phenomenon within its real life context. SenseCam therapy aimed to stimulate the cognition of a person with dementia, with support of their personal identity as its primary goal. SenseCam images were used as cues to meaningful discussions about the person’s recent memories. The images enabled a construction of a particular version of the participants’ identities mainly based in their recent past. On the contrary participants seemed to valorise their identity of their distant past. The SenseCam identity also contained uncensored details from participants’ lives as revealed by review of SenseCam images. The exposing nature of SenseCam images posed risks to the users’ privacy and showed the potential ethical risks of using lifelogging technology with people with dementia. There is limited literature on the practical recommendations on how to use lifelogging devices and how they affect people with dementia. The results from this research indicate that a number of factors should be considered when using lifelogging technology with people with dementia. Firstly the contextual factors of people with dementia including the level of cognitive impairment, existing coping mechanisms and the interaction patterns with the carer need to be considered. Secondly the technology should be used within a therapeutic framework and tailored to suit the individual needs of both people with dementia and their carers. Lastly intimate and unexpected details from the participant’s life should be discussed in an ethical and sensitive manner. Implications of not working within these boundaries show clear potential for undermining the human rights and potentially the wellbeing of people with dementia

    Exploring the Design Space of Mobile Applications for Addressing Depression-associated Autobiographical Memory Impairments

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    Depression is an affective disorder with a range of cognitive biases and distortions, which drives depression onset, development and maintenance. This PhD research aims to support end users with non-clinical depression, by exploring the possibility of mitigating a range of depression-associated impairments in autobiographical memory processing (D-ABMs) through mobile applications. Emerging psychological interventions targeting these disrupted D-ABMs issues hold enormous potential of mitigating depression symptoms and thus been widely explored in the field of psychology. However, they have received less support from HCI research in depression . Current HCI work on digital interventions mainly support the digitization of mainstream psychological interventions such as Cognitive Behavioural Therapy (CBT) as it is acknowledged as the most evidence-based interventions, and its pre-structured nature makes it easier to be transferred into digital app design. However, the pre-defined nature of CBT related interventions can also bring various limitations. Different to the pre-structured interventions such as CBT, D-ABMs interventions hold promises in bringing more person-centric training content that are more flexible to app users’ needs. This thesis aims to explore the design space of mobile apps for D-ABMs. For this purpose, first, I explored the key effective components in current depression interventions while addressing D-ABMs, and analysed how they can inform the design of apps for supporting these interventions. Then, I explored the combination of app features to be included in the design of D-ABM apps, which can support these therapeutic components. Finally, I investigated into an effective design method for helping future designers of D-ABM apps to utilise the empirical findings gained from this thesis work. Overall, this thesis provides empirical exploration and design perspective that demonstrate ways of adapting memory assistive technologies to support the mitigation of depression associated cognitive dysfunctions and consequently alleviating depressive symptoms. The work aims to draw attention to depression-associated cognitive impairments as a less explored space in the filed of HCI, and to inspire HCI researchers to develop novel classes of mobile-based technologies for addressing a wide range of cognitive impairments that are associated depression. The contribution of this thesis opens up new design opportunities for both memory assistive and depression management technologies. The work aims to broaden the awareness of HCI researchers of mental conditions that involve autobiographical memory impairments besides episodic memory loss, such as depression, PTSD, or anxiety, which can be benefited from memory technologies that tailored for each specific conditions

    Towards augmented human memory: Retrieval-induced forgetting and retrieval practice in an interactive, end-of-day review

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    We report six experiments that examined the contention that an end-of-day review could lead to augmentation in human memory. In Experiment 1, participants in the study phase were presented with a campus tour of different to-be-remembered objects in different university locations. Each to-be-remembered object was presented with an associated specific comment. Participants were then shown the location name and photographs of half of the objects from half of the locations, and they were asked to try to name the object and recall the associated comment specific to each item. Following a filled delay, participants were presented with the name of each campus location and were asked to free recall the to-be-remembered objects. Relative to the recall from the unpracticed location categories, participants recalled the names of significantly more objects that they practiced (retrieval practice) and significantly fewer unpracticed objects from the practiced locations (retrieval-induced forgetting, RIF). These findings were replicated in Experiment 2 using a campus scavenger hunt in which participants selected their own stimuli from experimenter’s categories. Following an examination of factors that maximized the effects of RIF and retrieval practice in the laboratory (Experiment 3), we applied these findings to the campus scavenger hunt task to create different retrieval practice schedules to maximize and minimize recall of items based on experimenter-selected (Experiment 4) and participant-selected items using both category-cued free recall (Experiment 5) and item-specific cues (Experiment 6). Our findings support the claim that an interactive, end-of-day review could lead to augmentation in human memory

    Communicating with your E-memory: finding and refinding in personal lifelogs

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    The rapid development of technology enables the digital capture and storage of our life experiences in an “E-Memory” (electronic–memory) or personal lifelog (PLL). This offers the potential for people to store the details of their life in a permanent archive, so that the information is still available even when its physical existence has vanished and when memory traces of it have faded away. A major challenge for PLLs is enabling people to access information when it is needed. Many people may also want to share or transfer some of their memory to their friends and descendants, so that their experiences can be appreciated and their knowledge can be kept even after they have passed away. This thesis further explores people’s potential needs from their own PLLs, discuss the possible methods people may use and potential problems that they may encounter while accessing their PLLs, and hypothesize that better support of users’ own memory can provide better user experience and improved efficiency for accessing their E-memories (or PLLs). As part of a larger project, three lifeloggers collected their own prototype lifelog collection for about 20 months’ time. To complete this study, the author developed a prototype PLL system, called the iCLIPS Lifelog Archive Browser (LAB), based on the author’s theoretical exploration and empirical studies, and evaluated it using our prototype lifelog collections through a user study with the three lifeloggers. The results of this study provide promising evidence which support the hypothesis. The end of this thesis also discusses the issues that the lifeloggers encountered in using their lifelogs and future technologies that are desirable based the studies in this thesis
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