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Journal articles on the topic 'Smartwatch visualization'

Author: Grafiati

Published: 25 May 2024

Last updated: 31 July 2025

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1

Dong, Miaomiao, Ze Bian, and Yuan Zhu. "From data collection to design principles: A study of smartwatch faces for enhanced information visualization." PLOS One 20, no. 7 (2025): e0327647. https://doi.org/10.1371/journal.pone.0327647.

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With the surge in smartwatch popularity, presenting diverse data on a compact screen poses significant challenges. Previous research has primarily focused on the visual design of smartwatch faces, with limited exploration into how information interacts with users. Moreover, these studies have inadequately addressed interaction and practicality in information visualization. Our work analyzed 518 Huawei and 435 Facer smartwatch faces, synthesizing existing design elements and integrating insights from prior literature to propose a structured design framework that encompasses five key dimensions:

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2

Cui, Zhe, Shivalik Sen, Sriram Karthik Badam, and Niklas Elmqvist. "VisHive: Supporting web-based visualization through ad hoc computational clusters of mobile devices." Information Visualization 18, no. 2 (2018): 195–210. http://dx.doi.org/10.1177/1473871617752910.

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Current web-based visualizations are designed for single computers and cannot make use of additional devices on the client side, even if today’s users often have access to several, such as a tablet, a smartphone, and a smartwatch. We present a framework for ad hoc computational clusters that leverage these local devices for visualization computations. Furthermore, we present an instantiating JavaScript toolkit called VisHive for constructing web-based visualization applications that can transparently connect multiple devices—called cells—into such ad hoc clusters—called a hive—for local comput

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3

Ramakrishnan, R., and P. Angarika. "SMART WATCH DATA ANALYSIS USING PYTHON AND HUMAN HEALTH PREDICTION." International Scientific Journal of Engineering and Management 03, no. 12 (2024): 1–5. https://doi.org/10.55041/isjem02154.

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This project leverages smartwatch fitness data to predict health patterns and monitor daily activity trends, underscoring the role of wearables in personal health management. Using Python, Pandas, and Plotly, it handles data preprocessing, visualization, and predictive analysis on metrics such as step counts, calories burned, and active minutes. Data preprocessing includes managing missing values and standardizing the "Activity Date" field. Descriptive statistics and visualizations, including scatter plots, pie charts, and bar charts, uncover trends and behavioral patterns. Descriptive statist

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Dey, Bijoy Kumar, Ritika Khan, and Mainak Kunai. "Analysis of Fitness Based on Smart Watch Data." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 02 (2024): 1–10. http://dx.doi.org/10.55041/ijsrem28514.

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Smart watch, a new trend to many young as well as aged persons now a days, can serve as a fitness tracker and be far more accurate than a phone. Besides many technological advantages, a smartwatch can easily collect the data related to fitness and other movements also. Smart watch provides such an organized human health and activities dataset so that by this dataset a human activities analysis can be performed and by this analysis a conclusion can be drawn about their health. Accordingly, our Project aim is to analyze the data and examine whether the data collected through smart watches can de

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Hidayaturrohman, Qisthi Alhazmi, M. Arifudin Lukmana, and Akhmad Nidhomuz Zaman. "Design of human heartbeat monitoring system based on wireless sensor networks." Techné : Jurnal Ilmiah Elektroteknika 22, no. 2 (2023): 207–16. http://dx.doi.org/10.31358/techne.v22i2.354.

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The IoT technology plays an important role in Industry 4.0 revolution. The IoT technology has potential to be implemented in the medical industry, especially for the development of telemedicine system. IoT able to send the medical sensor data wirelessly to the nearest medical facility like hospital. In this research, the author designed the heart beat monitoring system by using 802.11 communication protocol and simple web interface. The pulse sensor that used in this research was able to read the pulse rate of the human and convert it to BPM (beat per minute). It has 98.89% accuracy and 1.11%

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Blascheck, Tanja, Lonni Besancon, Anastasia Bezerianos, Bongshin Lee, and Petra Isenberg. "Glanceable Visualization: Studies of Data Comparison Performance on Smartwatches." IEEE Transactions on Visualization and Computer Graphics 25, no. 1 (2019): 630–40. http://dx.doi.org/10.1109/tvcg.2018.2865142.

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7

Santhanavanich, T., S. Schneider, P. Rodrigues, and V. Coors. "INTEGRATION AND VISUALIZATION OF HETEROGENEOUS SENSOR DATA AND GEOSPATIAL INFORMATION." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4/W7 (September 20, 2018): 115–22. http://dx.doi.org/10.5194/isprs-annals-iv-4-w7-115-2018.

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<p><strong>Abstract.</strong> According to the advances in Information &amp; Communication Technology (ICT), nowadays, the use of Internet of Things (IoT) has become a normal part of daily life. It allows interconnections among a wide variety of devices and sensors such as smartphones, smartwatches, automobiles, or any object with a built-in sensor. However, these devices and sensors are developed by numerous different manufacturers which leads to technology lock-in in terms of data formats and protocols. In order of address this heterogeneity, an interoperable sensor pro

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8

Hashimoto, Yoshiki, Daisaku Arita, Atsushi Shimada, et al. "Yield Visualization Based on Farm Work Information Measured by Smart Devices." Sensors 18, no. 11 (2018): 3906. http://dx.doi.org/10.3390/s18113906.

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This paper proposes a new approach to visualizing spatial variation of plant status in a tomato greenhouse based on farm work information operated by laborers. Farm work information consists of a farm laborer’s position and action. A farm laborer’s position is estimated based on radio wave strength measured by using a smartphone carried by the farm laborer and Bluetooth beacons placed in the greenhouse. A farm laborer’s action is recognized based on motion data measured by using smartwatches worn on both wrists of the farm laborer. As experiment, harvesting information operated by one farm lab

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9

Chong-White, Nicky, Joseph Tagudin, and Jorge Mejia. "Advancing hearing research with the NAL ecologically momentary assessment platform for real-world insights." Journal of the Acoustical Society of America 154, no. 4_supplement (2023): A206—A207. http://dx.doi.org/10.1121/10.0023293.

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Ecological Momentary Assessment (EMA) is an invaluable tool for assessing people's behaviours and experiences in their natural surroundings. We have developed a smartphone-based EMA tool, called NEMA, that has contributed to over 10 research studies by providing meaningful real-world insights into how individuals with hearing loss interact with various hearing device technologies. By providing real-world perspectives that complement traditional lab-based tests, NEMA offers a more comprehensive understanding of everyday hearing and communication challenges. Its advanced features include cloud-c

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So, Junyong, Sekyoung Youm, and Sojung Kim. "A Human Body Simulation Using Semantic Segmentation and Image-Based Reconstruction Techniques for Personalized Healthcare." Applied Sciences 14, no. 16 (2024): 7107. http://dx.doi.org/10.3390/app14167107.

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The global healthcare market is expanding, with a particular focus on personalized care for individuals who are unable to leave their homes due to the COVID-19 pandemic. However, the implementation of personalized care is challenging due to the need for additional devices, such as smartwatches and wearable trackers. This study aims to develop a human body simulation that predicts and visualizes an individual’s 3D body changes based on 2D images taken by a portable device. The simulation proposed in this study uses semantic segmentation and image-based reconstruction techniques to preprocess 2D

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11

Pérez, Cristina T., Stephanie T. Salling, and Søren Wandahl. "Location-based Work Sampling." Lean Construction Journal 2023 (December 31, 2023): 69–81. http://dx.doi.org/10.60164/6ysp7wio4.

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Question: Which opportunities can merging geographic location data with Work Sampling (WS) data bring for construction management? Purpose: To identify which opportunities adding geographic information to the random observations made (named in this study as geo-located observations) can bring. Research Method: The authors presented the implementation of a novel adaptation of the WS technique, named Location-Based Work Sampling (LBWS), based on the findings from a Case Study. The research process followed four steps: (1) clarifying the categories of the activities; (2) deciding the confidence i

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12

Abdelhamid, Khaled, Pamela Reissenberger, Diana Piper, et al. "Fully Automated Photoplethysmography-Based Wearable Atrial Fibrillation Screening in a Hospital Setting." Diagnostics 15, no. 10 (2025): 1233. https://doi.org/10.3390/diagnostics15101233.

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Background/Objectives: Atrial fibrillation (AF) remains a major risk factor for stroke. It is often asymptomatic and paroxysmal, making it difficult to detect with conventional electrocardiography (ECG). While photoplethysmography (PPG)-based devices like smartwatches have demonstrated efficacy in detecting AF, they are rarely integrated into hospital infrastructure. The study aimed to establish a seamless system for real-time AF screening in hospitalized high-risk patients using a wrist-worn PPG device integrated into a hospital’s data infrastructure. Methods: In this investigator-initiated p

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13

Shandhi, Md Mobashir Hasan, Jennifer C. Goldsack, Kyle Ryan, et al. "Recent Academic Research on Clinically Relevant Digital Measures: Systematic Review." Journal of Medical Internet Research 23, no. 9 (2021): e29875. http://dx.doi.org/10.2196/29875.

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Background Digital clinical measures collected via various digital sensing technologies such as smartphones, smartwatches, wearables, ingestibles, and implantables are increasingly used by individuals and clinicians to capture health outcomes or behavioral and physiological characteristics of individuals. Although academia is taking an active role in evaluating digital sensing products, academic contributions to advancing the safe, effective, ethical, and equitable use of digital clinical measures are poorly characterized. Objective We performed a systematic review to characterize the nature o

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14

Ankrah, Elizabeth A., Franceli L. Cibrian, Lucas M. Silva, et al. "Me, My Health, and My Watch: How Children with ADHD Understand Smartwatch Health Data." ACM Transactions on Computer-Human Interaction, December 20, 2022. http://dx.doi.org/10.1145/3577008.

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Children with ADHD can experience a wide variety of challenges related to self-regulation, which can lead to poor educational, health, and wellness outcomes. Technological interventions, such as mobile and wearable health systems, can support data collection and reflection about health status. However, little is known about how ADHD children interpret such data. We conducted a deployment study with 10 children, aged 10 to 15, for six weeks, during which they used a smartwatch in their homes. Results from observations and interviews during this study indicate that children with ADHD can interpr

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15

Jin, Wenkui, and Wanlin Deng. "Research on the design of smartwatch health information visualization presentation under different motion scenarios." Scientific Reports 15, no. 1 (2025). https://doi.org/10.1038/s41598-025-12226-w.

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16

LeBaron, Virginia, Natalie Crimp, Nutta Homdee, et al. "“Less words, more pictures”: creating and sharing data visualizations from a remote health monitoring system with clinicians to improve cancer pain management." Frontiers in Digital Health 7 (April 23, 2025). https://doi.org/10.3389/fdgth.2025.1520990.

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BackgroundThe Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C) is a remote health monitoring system (RHMS) developed by our interdisciplinary team that collects holistic physiological, behavioral, psychosocial, and contextual data related to pain from dyads of patients with cancer and their family caregivers via environmental and wearable (smartwatch) sensors.MethodsR, Python, and Canva software were used to create a series of static and interactive data visualizations (e.g., visual representations of data in the form of graphs, figures, or pictures) from de-identified

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17

Spaccarotella, C., P. A. Polimeni Alberto, F. D. Ferraro Daniel, et al. "Smart watch for the detection of exercise-induced transient ST segment changes." European Heart Journal 45, Supplement_1 (2024). http://dx.doi.org/10.1093/eurheartj/ehae666.3440.

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Abstract Background Smartwatches are largely used and allowed to perform electrocardiogram one lead, usually a modified DI, used to diagnose atrial fibrillation. It is unknown whether or not smartwatches could be used to identify electrocardiographic transient ST changes during exercise-induced myocardial ischemia. The present study assessed the feasibility and reliability of using an Apple watch to record V5 in subjects scheduled for standard ECG stress tests. Methods One hundred eighty-nine subjects were included in this study. The mean age was 61+9 years, and 21.6 % were women (41 subjects)

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18

Reithe, Haakon, Brice Marty, Juan C. Torrado, et al. "Cross-evaluation of wearable data for use in Parkinson’s disease research: a free-living observational study on Empatica E4, Fitbit Sense, and Oura." BioMedical Engineering OnLine 24, no. 1 (2025). https://doi.org/10.1186/s12938-025-01353-0.

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Abstract Background Established assessment scales used for Parkinson’s disease (PD) have several limitations in tracking symptom progression and fluctuation. Both research and commercial-grade wearables show potential in improving these assessments. However, it is not known whether pervasive and affordable devices can deliver reliable data, suitable for designing open-source unobtrusive around-the-clock assessments. Our aim is to investigate the usefulness of the research-grade wristband Empatica E4, commercial-grade smartwatch Fitbit Sense, and the Oura ring, for PD research. Method The study

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19

Dong, Miaomiao. "Investigating the Users’ Preferences of Heart Rate Data Types and Visualizations on a Smartwatch." International Journal of Human–Computer Interaction, July 18, 2023, 1–22. http://dx.doi.org/10.1080/10447318.2023.2233130.

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20

Ford, Colby T., Jake A. Galler, Yingnan He, et al. "Using Apple Watches to Monitor Health and Behaviors of Individuals with Cognitive Impairment: A Case Series Study." Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, October 30, 2024. http://dx.doi.org/10.1093/gerona/glae250.

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Abstract Objectives This study explores the potential of developing digital biomarkers from wearables for monitoring individuals with Alzheimer’s Disease and Related Dementias, focusing on the feasibility of using Apple Watches for tracking health and behaviors in older adults with cognitive impairment. Method Data collection used the Amissa Health technology stack, which passively collects time-series data from smartwatches and provides a high-frequency cloud database for secure data storage, query, and visualization by clinicians and researchers. The platform consists of i) AmissaWear, a sof

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21

Dorsch, Michael, Jessica Golbus, Tanima Basu, et al. "Abstract 25: The Blood Pressure Effects of a Just-in-time-adaptive Intervention for Physical Activity and Diet in Patients with Hypertension: A Randomized Controlled Trial." Hypertension 81, Suppl_1 (2024). http://dx.doi.org/10.1161/hyp.81.suppl_1.25.

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Background: Emerging data suggest mobile health interventions are a promising approach for managing hypertension, but large-scale studies are lacking. The myBPmyLife mobile application is a just-in-time adaptive intervention incorporating behavioral change strategies such as goal setting, prompts, visualizations, and feedback to encourage increased physical activity and lower-sodium food choices. Methods: The study was a prospective, randomized-controlled trial that enrolled patients with hypertension from the University of Michigan Health in Ann Arbor, MI, and the Hamilton Community Health Ne

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22

LeBaron, Virginia, Nutta Homdee, Emmanuel Ogunjirin, Nyota Patel, Leslie Blackhall, and John Lach. "Describing and visualizing the patient and caregiver experience of cancer pain in the home context using ecological momentary assessments." DIGITAL HEALTH 9 (January 2023). http://dx.doi.org/10.1177/20552076231194936.

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Background Pain continues to be a difficult and pervasive problem for patients with cancer, and those who care for them. Remote health monitoring systems (RHMS), such as the Behavioral and Environmental Sensing and Intervention for Cancer (BESI-C), can utilize Ecological Momentary Assessments (EMAs) to provide a more holistic understanding of the patient and family experience of cancer pain within the home context. Methods Participants used the BESI-C system for 2-weeks which collected data via EMAs deployed on wearable devices (smartwatches) worn by both patients with cancer and their primary

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