Childhood obesity and related costs are increasing worldwide [1-3]. It has been shown that the majority of children with obesity remained obese in adulthood, resulting in significant health care costs [4]. Promoting better diet and regular physical activities [5] can help prevent childhood obesity and thus reduce the occurrence of obesity-related metabolic and cardiovascular diseases [6], and in turn reduce health care costs.

Management of childhood obesity usually involves patient lifestyle counseling [7], but face-to-face counseling can be expensive and difficult for patients in rural areas [5]. There is a growing emphasis on patient-centered health care, where care extends beyond the hospital and is “respectful of and responsive to individual patient preferences, needs, values, and ensuring that patient values guide all clinical decisions”[8]. A promising solution for patient-centered care is the deployment of connected health technologies for remote diagnosis, monitoring, and treatment and patient self-care and support [9,10]. The tracking of physical activity has been studied extensively since the 2000s [11]. It is only in the previous 5 years that wearables, such as wristwatches with activity sensors, have become sophisticated enough to provide measures beyond steps, distance, calories, and sleep. For example, wearables can now measure activity minutes, heart rate, and goal and target-oriented designs [12]. These advances in wearables allow more accurate tracking of physical activities and provide greater insight into the type and form of physical activity undertaken by the user, such as exercise intensity and metabolic rate [13].

The use of these wearables can further be enhanced through integration with the Internet of Things (IoT) [14]. Since the advent of IoT in 1999 [15], IoT-enabled devices and networks have been applied to a range of applications including smart cities [16], virtual power plants [17], and health care [18,19]. In the health care setting, IoT-enabled devices—technologies that are connected to a network–can give accurate and real-time feedback that can generate health data to improve understanding of user behavior and personalize treatment regimes. Acampora et al [20] surveyed the applications of IoT in health care and identified six main applications in health care (Table 1).

Technologies that track physical activity are widely used in health care applications. Previous studies have reviewed different applications of IoT and non-IoT physical activity trackers for various patient groups, including patients with rheumatic and musculoskeletal diseases [21], epilepsy, Parkinson, patients who have had a stroke [22], working-age women [23], people with serious mental illness [24], obese adults [25], and children [26,27]. These wearable activity trackers have generally shown significant effectiveness in increasing physical activity in the short-term [28], but there are still relatively few studies justifying their long term effectiveness [29]. Furthermore, long-term user adherence remains challenging [30].

Most systematic reviews on physical activity tracking and weight management in children were published several years ago. However, one recent review examined the feasibility and effectiveness of wearable activity trackers for young people (5-19 years old) [27]. Overall, they found that measures of effectiveness were mostly positive but nonsignificant. However, this review included any type of wearable activity tracker and did not focus on IoT.

With regard to user perspectives of mobile health interventions for weight management, it was found that user acceptance of trackers can vary greatly depending on their age group [31,32]. In addition, although the data from wearables can be a valuable source of data for diagnosis and patient monitoring, they are oftentimes not standardized or validated, which limits their clinical significance in supporting clinical decision making [22,33].

There is a gap in the literature regarding children and adolescent’s use of digital weight management technologies that are connected to a wider network. Currently, no studies focusing on the wider context of IoT-enabled technologies for weight management in children and adolescents have been published. Previously published reviews have focused on elements of this (ie, weight management in children and adolescents, the use of IoT in weight management technologies), but none have examined the intersection. This review will aim to understand how IoT-enabled technologies designed for youth, such as physical activity trackers and weight management apps, fit in the wider IoT context, how data obtained through these devices can improve health care delivery, and whether these address privacy concerns by considering regulations. Specifically, the review aims to answer the following questions:

This protocol is developed in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement [34] and the systematic review to be executed based on this protocol will also be conducted in accordance with PRISMA.

We will search Medline, Pubmed, Web of Science, Scopus, ProQuest Central, Engineering Village Compendex, and the IEEE Xplore Digital Library for studies published after 2010 using a combination of keywords and subject headings related to health activity tracking, youth, and IoT (Table 2). The search string will be constructed in this format: (Health activity tracking) AND (Youth) AND (IoT). Additionally, a Google search will be used to identify gray literature. A sample search conducted in Medline can be found in Multimedia Appendix 1.

The study was defined as follows using the PICO (population, intervention, comparator, outcomes) model:

The inclusion and exclusion criteria for the study can be found in Textbox 1.