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Wearable medical devices (WMDs) are improving people’s health and well-being in a noble way, as these aid in effective personal health monitoring, remote surveillance and overall illness management. Despite its wider applicability and usage, it is prevalent that users discontinue its usage, which presents an obstacle in the proliferation of such vital innovations among the masses. Therefore, relying on the expectation-confirmation model (ECM), this study aims to delve deeper to explain the factors that motivate users to continually use WMDs by incorporating novel variables, namely, health belief, health information accuracy and privacy protection.

The study proposes and tests an extended ECM perspective to predict the continuance intention (CI) of WMDs among users. By using structural equation modelling using SmartPLS, the authors tested the model on Indian people (n = 451) who had an erstwhile experience of using WMDs.

The study results show that confirmation of users’ expectations positively impacts their usefulness and satisfaction towards WMDs. Moreover, satisfaction towards WMDs is the strongest predictor of users’ CI, followed by perceived usefulness. Interestingly, personal factor such as health beliefs reveals a greater influence on perceived usefulness than technological factors like health information accuracy and privacy protection.

The study findings demonstrate the significance of using the expectation-confirmation perspective in technology-based studies in general and WMDs, in particular. This study aids by offering an integrated model of WMD’s continued usage intention for the users, in addition to practical implications for marketers and policymakers.

A paucity of research exists when understanding the predictors of CI for WMDs. This study fills this gap and adds to behavioural literature by offering a noble viewpoint involving an extended ECM perspective.

This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

The purpose of this study is to identify the major factors influencing the adoption of health-care wearables in generation Z (Gen Z) customers in India. A conceptual framework using push pull and mooring (PPM) adoption theory was developed.

Data was collected from 208 Gen Z customers based on 5 constructs related to the adoption of health-care wearables. Confirmatory factor analysis and structural equation modelling was used to analyse the responses. The mediation paths were analysed using bootstrapping method and examination of the standardized direct and indirect effects in the model.

The study results indicated that the antecedent factors consisted of push (real-time health information availability), pull (normative environment) and mooring (decision self-efficacy) factors. The mooring factor (MOOR) was related to the push factor but not the pull factor. The MOOR, in turn, was related to the switching intention of Gen Z customers for health wearables adoption.

The research study extended the literature related to the PPM theory in the context of the adoption of health wearables among Gen Z customers in India.

The study outcome would enable managers working in health wearable organizations to understand consumer behaviour towards health wearables.

The use of health wearables among Gen Z individuals would lead to future generations adopting a healthy lifestyle resulting in an effective workforce and better economy.

This was one of the few studies which have explored the PPM theory to explore the factors for the adoption of health wearables among Gen Z customers in India.

This research was to understand people's perceptions and trends in wearable robots and the research questions were as follows: (1) investigating key terms related to wearable robots that were frequently used by and exposed to people and (2) analyzing relationships among those key terms.

Textom, a big data collection and analysis software system, was used to collect data using the keyword – wearable robot.

The frequency-inverse document frequency, term frequency and central analyses were investigated, and the major key terms related to wearable robots and their connectivity were identified. After performing network analysis and convergence of iterated correlations analyses using UCINET and NetDraw programs, the major key term categories were identified.

It is important to understand how people think and perceive about wearable robots before developing wearable robots. The results of the research are expected to be helpful to better understand how people perceive and what key terms are mainly discussed by people in both countries and ultimately help when developing wearable robots with better market targeting approach methods.

This paper aims to provide a review of different types of non-wearable human identification sensors which can be applied for smart home environment.

The authors performed a systematic review to assess and compare different types of non-wearable and non-intrusive human identification sensors used in smart home environment. The literature research adds up to 5,567 records from 2000 to 2016, out of which 40 articles were screened and selected for this review.

In this review, the authors classified non-wearable human identification technologies into four main groups, namely, object-based, footstep-based, body shape-based and gait-based identification technologies. Assessing these four group of identification technologies showed that the maturity of non-wearable identification is not high and most of these technologies are verified in a lab environment. Additionally, footstep-based identification is the most popular identification approach listed in the literature.

This study contributes to the literature on human identification technologies in several ways. This paper identifies the state-of-the-art regarding non-wearable technologies which can be used in smart home environment. Moreover, the results of this paper can provide a better understanding of advantages and disadvantages of the non-wearable identification technologies.

This paper aims to investigate the key enablers and inhibitors that influence the intention to use fitness wearables using the value-based adoption model (VAM).

Data were collected using a structured online questionnaire from 323 respondents who had never used fitness wearables. A purposive sampling technique was used in this study. Smart PLS was employed to test the research framework and hypotheses using a two-step approach.

The findings support some of the hypotheses developed with R² values of 0.622 for perceived value (PV) and 0.567 for intention to use fitness wearable. Perceived enjoyment, perceived social image and perceived usefulness had a positive effect on PV. In addition, health information sensitivity (HIS) was positively related to perceived privacy risk and health information accuracy was positively related to perceived usefulness. Surprisingly, this study did not find any significant relationship between perceived fee, perceived privacy risk, perceived health increase and perceived design aesthetics with PV.

This study's findings can help designers and manufacturers design fitness wearables by considering factors that users find valuable, thus satisfying consumers' needs.

This study tries to model behavioural intention of fitness wearable usage of individual users by using the VAM with the addition of two new antecedences, HSI and health information accuracy, to better explain the behaviour.

The purpose of this study was to identify the major quality features of wearable technology embedded products that have the greatest impact on consumer satisfaction using the Kano model, an organized approach to specify consumer requirements and expectation through a preference classification technique.

Using a quantitative research method, an online survey was conducted with a convenience sample of US consumers aged between 19 years old and over. A total of otal 471 useable data were obtained and used for the data analysis.

This study identified that the 11 quality features of wearables belong to one-dimensional quality category among the five Kano categories, although the impact of each quality feature's performance on consumer satisfaction varies. The results also showed that the performance level of durability, long battery life, usability, product safety, comfortability and reasonable price has the greatest impact on consumer satisfaction of wearables.

This study has implications for future research by integrating the Kano model with other design and product development related theoretical models when designing, developing and evaluating various wearable products.

This study quantified the key quality features of wearables using the Kano model, which can be a great measurement tool for future researchers to adopt in their studies. The findings of this study help designers, developers and producers of wearables to prioritize the quality features during the product design, development and manufacturing process.

Construction organizations must maintain a productive workforce without sacrificing their health and safety. The global construction sector loses billions of dollars yearly to poor health and safety practices. This study aims to investigate benefits derivable from using wearable technologies to improve construction health and safety. The study also reports the challenges associated with adopting wearable technologies.

The study adopted a quantitative design, administering close-ended questions to professionals in the Nigerian construction industry. The research data were analysed using descriptive and inferential statistics.

The study found that the critical areas construction organizations can benefit from using WSDs include slips and trips, sensing environmental concerns, collision avoidance, falling from a high level and electrocution. However, key barriers preventing the organizations from adopting wearable technologies are related to cost, technology and human factors.

The time and cost lost to H&S incidents in the Nigerian construction sector can be reduced by implementing the report of this study.

Studies on WSDs have continued to increase in developed countries, but Nigeria is yet to experience a leap in the research area. This study provides insights into the Nigerian reality to provide directions for practice and theory.

Introduction: There is a variety of wearables and health applications available in the market which allow the tracking of various health and lifestyle measures like blood sugar, calorie counter, number of steps, sleep patterns, etc. After the Covid-19 pandemic, people have become more aware of their health and use these wearables to maintain a healthy lifestyle. Insurance companies in India are also eyeing the potential usage of these wearables in life and health insurance.

Purpose: This research aims to look at the emergence of wearables and health apps and their usage in India’s life and health insurance industry. This study also focuses on how these devices might benefit insurers’ business models and some of the pitfalls to consider.

Methodology: The study used both primary and secondary data. A survey was conducted to understand the customer perception towards usage of wearables. The secondary research included the analysis of the integration of wearables by insurance companies.

Findings: The research would be helpful to the insurance companies as it would help them to understand the customer’s viewpoint for the usage of wearables in the insurance industry. This study would also allow insurers to understand new dimensions, such as where the wearables improve customer satisfaction and engagement. The study results would be helpful for the customers for the appropriate usage of wearables and the internet of things (IoT). Insurance companies can provide better pricing and make personalised insurance plans that ultimately help customers.