Digital Behavior Change Intervention Designs for Habit Formation: Systematic Review.

BACKGROUND: With the development of emerging technologies, digital behavior change interventions (DBCIs) help to maintain regular physical activity in daily life. OBJECTIVE: To comprehensively understand the design implementations of habit formation techniques in current DBCIs, a systematic review was conducted to investigate the implementations of behavior change techniques, types of habit formation techniques, and design strategies in current DBCIs. METHODS: The process of this review followed the PRISMA (Preferred Reporting Item for Systematic Reviews and Meta-Analyses) guidelines. A total of 4 databases were systematically searched from 2012 to 2022, which included Web of Science, Scopus, ACM Digital Library, and PubMed. The inclusion criteria encompassed studies that used digital tools for physical activity, examined behavior change intervention techniques, and were written in English. RESULTS: A total of 41 identified research articles were included in this review. The results show that the most applied behavior change techniques were the self-monitoring of behavior, goal setting, and prompts and cues. Moreover, habit formation techniques were identified and developed based on intentions, cues, and positive reinforcement. Commonly used methods included automatic monitoring, descriptive feedback, general guidelines, self-set goals, time-based cues, and virtual rewards. CONCLUSIONS: A total of 32 commonly design strategies of habit formation techniques were summarized and mapped to the proposed conceptual framework, which was categorized into target-mediated (generalization and personalization) and technology-mediated interactions (explicitness and implicitness). Most of the existing studies use the explicit interaction, aligning with the personalized habit formation techniques in the design strategies of DBCIs. However, implicit interaction design strategies are lacking in the reviewed studies. The proposed conceptual framework and potential solutions can serve as guidelines for designing strategies aimed at habit formation within DBCIs.

Motion Tracking of Daily Living and Physical Activities in Health Care: Systematic Review From Designers' Perspective.

BACKGROUND: Motion tracking technologies serve as crucial links between physical activities and health care insights, facilitating data acquisition essential for analyzing and intervening in physical activity. Yet, systematic methodologies for evaluating motion tracking data, especially concerning user activity recognition in health care applications, remain underreported. OBJECTIVE: This study aims to systematically review motion tracking in daily living and physical activities, emphasizing the critical interaction among devices, users, and environments from a design perspective, and to analyze the process involved in health care application research. It intends to delineate the design and application intricacies in health care contexts, focusing on enhancing motion tracking data's accuracy and applicability for health monitoring and intervention strategies. METHODS: Using a systematic review, this research scrutinized motion tracking data and their application in health care and wellness, examining studies from Scopus, Web of Science, EBSCO, and PubMed databases. The review used actor network theory and data-enabled design to understand the complex interplay between humans, devices, and environments within these applications. RESULTS: Out of 1501 initially identified studies, 54 (3.66%) were included for in-depth analysis. These articles predominantly used accelerometer and gyroscope sensors (n=43, 80%) to monitor and analyze motion, demonstrating a strong preference for these technologies in capturing both dynamic and static activities. While incorporating portable devices (n=11, 20%) and multisensor configurations (n=16, 30%), the application of sensors across the body (n=15, 28%) and within physical spaces (n=17, 31%) highlights the diverse applications of motion tracking technologies in health care research. This diversity reflects the application's alignment with activity types ranging from daily movements to specialized scenarios. The results also reveal a diverse participant pool, including the general public, athletes, and specialized groups, with a focus on healthy individuals (n=31, 57%) and athletes (n=14, 26%). Despite this extensive application range, the focus primarily on laboratory-based studies (n=39, 72%) aimed at professional uses, such as precise activity identification and joint functionality assessment, emphasizes a significant challenge in translating findings from controlled environments to the dynamic conditions of everyday physical activities. CONCLUSIONS: This study's comprehensive investigation of motion tracking technology in health care research reveals a significant gap between the methods used for data collection and their practical application in real-world scenarios. It proposes an innovative approach that includes designers in the research process, emphasizing the importance of incorporating data-enabled design framework. This ensures that motion data collection is aligned with the dynamic and varied nature of daily living and physical activities. Such integration is crucial for developing health applications that are accessible, intuitive, and tailored to meet diverse user needs. By leveraging a multidisciplinary approach that combines design, engineering, and health sciences, the research opens new pathways for enhancing the usability and effectiveness of health technologies.

The Correlation of Regional Microstructure and Mechanics of the Cervical Articular Process in Adults.

PURPOSE: Using micro-CT and finite element analysis to establish regional variation microarchitectures and correlation with mechanical properties of cervical articular facet trabecular bone to predict cervical spine security and material properties. METHODS: A total of 144 cervical articular processes (each articular was separate to four region of interest (ROI), superior-anterior (SA), superior-posterior (SP), inferior-anterior (IA), and inferior-posterior (IP) regions) specimens with a volume of 5 × 5 × 5 mm3 were scanned by micro-CT, and allowable stress and other mechanical properties parameters in each region were calculated after mechanical testing, then the effectiveness was verified of finite element models by ABAQUS software. RESULTS: Maximum and minimum values of C2-C7 articular processes and regions are C5 and C7 level, SA and SP regions for bone volume fraction (BV/TV) and trabecular thickness (Tb.Th), whose variation tendency is similar to the Young's modulus, allowable stress, BMD, maximum force and strain. Between Young's modulus and all microstructure parameters, especially between BV/TV, bone mineral density (BMD) and Tb.Th, had higher linear regression coefficients R2 = 0.5676, 0.6382, 0.3535, respectively. BMD and yield strength, BV/TV, and allowable stress also had better regression coefficients, R2 = 0.5227, 0.5259, 0.5426, respectively. CONCLUSIONS: The contribution of the microstructure and mechanical properties of the C2-C7 cervical spine to the movement of the cervical spine is different and has a good correlation and the effectiveness of the finite element model is also verified that we can correctly calculate the microstructure and mechanical properties of the cervical articular process to evaluate the stability and injury risk of cervical vertebrae by the established model.

The Virtual-Spine Platform-Acquiring, visualizing, and analyzing individual sitting behavior.

Back pain is a serious medical problem especially for those people sitting over long periods during their daily work. Here we present a system to help users monitoring and examining their sitting behavior. The Virtual-Spine Platform (VSP) is an integrated system consisting of a real-time body position monitoring module and a data visualization module to provide individualized, immediate, and accurate sitting behavior support. It provides a comprehensive spine movement analysis as well as accumulated data visualization to demonstrate behavior patterns within a certain period. The two modules are discussed in detail focusing on the design of the VSP system with adequate capacity for continuous monitoring and a web-based interactive data analysis method to visualize and compare the sitting behavior of different persons. The data was collected in an experiment with a small group of subjects. Using this method, the behavior of five subjects was evaluated over a working day, enabling inferences and suggestions for sitting improvements. The results from the accumulated data module were used to elucidate the basic function of body position recognition of the VSP. Finally, an expert user study was conducted to evaluate VSP and support future developments.