Lifelogging in User Experience Research: Supporting Recall and Improving Data Richness

Arvola, Mattias; Blomkvist, Johan; Wahlman, Fredrik

doi:10.1080/14606925.2017.1352898

Cited by 13 publications

(16 citation statements)

References 12 publications

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“…Review of photographs captured by wearable cameras has been shown to improve memory for the reviewed events in people with hippocampal amnesia and Alzheimer's disease, and the memory support provided by these cameras is greater than the memory support provided by other means, such as reviewing a written diary (Berry et al, 2007;Browne et al, 2011;Loveday & Conway, 2011;Pauly-Tackacs, Moulin, & Estlin, 2011;Woodberry et al, 2015). Similar effects have also been observed in cognitively healthy young and older adults (Mair, Poirier, & Conway, 2017Sellen et al, 2007), and these findings have been documented systematically in a series of recent literature reviews (Allé et al, 2017;Arvola, Blomkvist, & Wahlman, 2017;Chow & Rissman, 2017;Dubourg, Silva, Fitamen, Moulin, & Souchay, 2016;Silva, Pinho, Macedo, & Moulin, 2016).…”

supporting

confidence: 72%

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Using a wearable camera to support everyday memory following brain injury: a single-case study

Mair

Shackleton

2021

Brain Impairment

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Background: Wearable cameras have been shown to improve memory in people with hippocampal amnesia and Alzheimer's disease. It is not known whether this benefit extends to people with amnesia of complex or uncertain origin. Method: This case study examined the effect of wearable camera use on memory and occupational performance in a patient with memory loss and complex mental health problems following a severe neurological incident. With the help of his occupational therapist (OT), Mr A used a wearable camera to record a series of eight personally significant events over a 6-week period. During visits from his OT, Mr A was asked to report what he could remember about the events, both before (baseline) and during the review of time-lapsed photographs captured automatically by the camera. Results: The results showed striking improvements in recall while reviewing the photographs, relative to baseline recall, but the additional details recalled during review did not appear to be maintained at later tests, after several days. Across the study period, there were moderate increases in occupational performance, measured using the Canadian Occupational Performance Measure. However, after the study period ended, Mr A ceased to use the wearable camera due to technological difficulty. Conclusion: There was a clear benefit of wearable camera use, but the real-world impact of the technology was limited by the complexity of the system. The results of the study are discussed alongside novel clinical insights and suggestions for developing wearable camera support systems that can be used independently by people with memory problems.

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confidence: 72%

“…reviews (Allé et al, 2017;Arvola, Blomkvist, & Wahlman, 2017;Chow & Rissman, 2017;Dubourg, Silva, Fitamen, Moulin, & Souchay, 2016;Silva, Pinho, Macedo, & Moulin, 2016).…”

mentioning

confidence: 99%

Using a wearable camera to support everyday memory following brain injury: a single-case study

Mair

Shackleton

2021

Brain Impairment

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“…One of the primary purposes of logging is to help viewers collect self-monitoring and reflection [75]. The real-time identification and tracking apps enable the monitoring and consumption of TV contents or other devices for the viewer through tracking pixels and cookies [76].…”

Section: Viewers Monitoringmentioning

confidence: 99%

Smart TV-Based Lifelogging Systems: Current Trends, Challenges, and the Road Ahead

Khan

Khusro

Alam

2021

Information and Knowledge in Internet of Things

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The phenomena of lifelogging can be described as "to digitally record the people's daily-life activities and events in varying amounts of detail" [1]. The lifelogging systems use various tools, applications, and devices, such as desktop computers, laptops, smartphones, wearable smart devices, biometric devices, and process the data for explaining the individual's daily-life activities [2]. This recorded information can offer the potential to mine or infer knowledge about life experiences and used for a variety of purposes including contextual recommendation, e-commerce, monitoring, memory augmentation, linking, summarization, contextual retrieval, browsing, the judicial system, searching, adaptive user interface, and analyzing user profiles [3]. Usually, these personalized devices captured a single user's events to help predict and find out different patterns, such as healthcare services, social network services, intelligent mirror services, and recommendation services. Moreover, a user must be actively involved during the lifelogging [4].Lifelogging is a form of pervasive computing. Users can digitally record, capture, store, archive, and process the individuals' complete life experiences in the form of multimodal through different sensors [5]. The main idea of lifelogging to enhance the way people record and exchange their data, information, communication with others, and log into tools or devices [6]. Besides, the concept of lifelogging, to gain knowledge and data about someone, is just like automated biography. However, the lifelogging applications/tools of these devices have been used for single-user life experiences. For example, lifelogging applications and computer tools, such as Latent [7], have their own perspective of live experiences. However, these

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“…People who keep lifelogs about themselves are known as lifeloggers [7]. The purpose of lifelogging is to help users collect data for self-monitoring and reflection [8]. Technology has nearly reached the stage when all information, interesting or otherwise, generated in a lifetime by a single person can be assembled and queried relatively efficiently, creating a need for personal information management [9].…”

Section: Introductionmentioning

confidence: 99%

Impact of Personal Health Records and Wearables on Health Outcomes and Patient Response: Three-Arm Randomized Controlled Trial

Kim¹,

Ryu²,

Cho³

et al. 2019

JMIR Mhealth Uhealth

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Background Although using the technologies for a variety of chronic health conditions such as personal health record (PHR) is reported to be acceptable and useful, there is a lack of evidence on the associations between the use of the technologies and the change of health outcome and patients’ response to a digital health app. Objective This study aimed to examine the impact of the use of PHR and wearables on health outcome improvement and sustained use of the health app that can be associated with patient engagement. Methods We developed an Android-based mobile phone app and used a wristband-type activity tracker (Samsung Charm) to collect data on health-related daily activities from individual patients. Dietary record, daily step counts, sleep log, subjective stress amount, blood pressure, and weight values were recorded. We conducted a prospective randomized clinical trial across 4 weeks on those diagnosed with obstructive sleep apnea (OSA) who had visited the outpatient clinic of Seoul National University Bundang Hospital. The trial randomly assigned 60 patients to 3 subgroups including 2 intervention groups: (1) mobile app and wearable device users (n=20), (2) mobile app–only users (n=20), and (3) controls (n=20). The primary outcome measure was weight change. Body weights before and after the trial were recorded and analyzed during clinic visits. Changes in OSA–related respiratory parameters such as respiratory disturbance, apnea-hypopnea, and oxygenation desaturation indexes and snoring comprised the secondary outcome and were analyzed for each participant. Results We collected the individual data for each group during the trial, specifically anthropometric measurement and laboratory test results for health outcomes, and the app usage logs for patient response were collected and analyzed. The body weight showed a significant reduction in the 2 intervention groups after intervention, and the mobile app–only group showed more weight loss compared with the controls ( P =.01). There were no significant changes in sleep-related health outcomes. From a patient response point of view, the average daily step counts (8165 steps) from the app plus wearable group were significantly higher than those (6034 steps) from the app-only group because they collected step count data from different devices ( P =.02). The average rate of data collection was not different in physical activity ( P =.99), food intake ( P =.98), sleep ( P =.95), stress ( P =.70), and weight ( P =.90) in the app plus wearable and app-only groups, respectively. Conclusions We tried to integrate PHR data that allow clinicians and patients to share lifelog data with the clinical workflow to support lifestyle interventions. Our results s...

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Lifelogging in User Experience Research: Supporting Recall and Improving Data Richness

Cited by 13 publications

References 12 publications

Using a wearable camera to support everyday memory following brain injury: a single-case study

Using a wearable camera to support everyday memory following brain injury: a single-case study

Smart TV-Based Lifelogging Systems: Current Trends, Challenges, and the Road Ahead

Impact of Personal Health Records and Wearables on Health Outcomes and Patient Response: Three-Arm Randomized Controlled Trial

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