Towards a Postphenomenological Approach to Wearable Technology through Design Journeys

Early diagnosis of Alzheimer's and epilepsy requires monitoring a subject's development of symptoms through electroencephalography (EEG) signals over long periods. Wearable devices enable convenient monitoring of biosignals, unlike complex and costly hospital equipment. The key to achieving a fit and forgettable wearable device is to increase its operating cycle and decrease its size and weight. Instead of batteries, which limit the life cycle of electronic devices and set their form factor, body heat and environmental light can power wearable devices through energy-scavenging technologies. The harvester transducers should be tailored according to on the application and the sensor placement. This leaves a wide variety of transducers with an extensive range of impedances and voltages. To realize an autonomous wearable device, the power converter energy harvester, has to be very efficient and maintain its efficiency despite potential transducer replacement or variations in environmental conditions. This thesis presents a detailed design of an efficient integrated power converter for use in an autonomous wearable device. The design is based on the examination of both power losses and power transfer in the power converter. The efficiency bound of the converter is derived from the specifications of its transducer. The tuning ranges for the reconfigurable parameters are extracted to keep the converter efficient with variations in the transducer specifications. With the efficient design and the manual tuning of the reconfigurable parameters, the converter can work optimally with different types of transducers, and keeps its efficiency in the conversion of low voltages from the harvesters. Measurements of the designed converter demonstrate an efficiency of higher than 50% and 70% with two different transducers having an open-circuit voltage as low as 20 mV and 100 mV, respectively. The power converter should be able to reconfigure itself without manual tunings to keep its efficiency despite changes in the harvesters' specifications. The second portion of this dissertation addresses this issue with a proposed design methodology to implement a control section. The control section adjusts the converter's reconfigurable parameters by examining the power transfer and loss and through concurrent closed loops. The concurrent loops working together raise a serious concern regarding stability. The system is designed and analyzed in the time domain with the state-space averaging (SSA) model to address the stability issue. The ultra-low-power control section obtained from the SSA model estimates the power and loss with a reasonable accuracy, and adjusts the timings in a stable manner. The entire control section consumes only 30 nW dynamic power at 10 kHz. The control section tunes the converter's speed or its working frequency depending on the available power. The frequency clocks the entire architecture, which is designed asynchronously; therefore, the power consumption of the system depends on the power available from the transducer. The system is implemented using 0.18 µm CMOS technology. For an input as low as 7 mV, the converter is not only functional but also has an efficiency of more than 40%. The efficiency can reach 70% with an input voltage of 50 mV. The system operates in a range of just a few of millivolts to half a volt with ample efficiencies. It can work at an optimal point with different transducers and environmental conditions.

Purpose The research provides new strategies for enhancing resilience in pharmaceutical manufacturing by addressing the dynamic nature of digital technology within the challenging framework of a VUCA (volatility, uncertainty, complexity and ambiguity) world, focusing on the concept of digital twins (DTs). This paper aims to emphasize the pivotal role of resilience in navigating disruptions and propose future research directions to contribute to the industry’s effective adaptation to uncertainties and dynamic challenges. Design/methodology/approach This research uses a qualitative approach, drawing insights from an extensive literature review on pharmaceutical manufacturing resilience and the integration of digital technologies. Methodologically, it synthesizes information from scholarly articles, empirical studies and industry reports to construct a comprehensive understanding. This design facilitates a thorough examination of the subject, providing valuable insights for practitioners, researchers and policymakers in the pharmaceutical industry. Findings This paper illustrates the practical application of DTs in vaccine production, emphasizing their critical role in ensuring quality, safety and adaptability. It adopts the “seizing, sensing and transforming” framework, showcasing the strategic integration of Industry 4.0 technologies to address dynamic challenges. Key insights include the significance of human elements alongside technological advancements, the need for real-time monitoring using Internet of Things (IoT) and artificial intelligence (AI) and the transformative potential of sustainability practices, diversified supply chains and collaborative ecosystems. Research limitations/implications This paper highlights the integration of human and digital elements, emphasizing IoT, AI and DTs for resilience. It underscores sustainable practices, supply chain diversification and collaboration as key strategies for addressing pharmaceutical industry challenges. Practical implications This paper offers practical insights for pharmaceutical manufacturing, emphasizing the need for robust cybersecurity measures, strategic investments in digital technologies and proactive regulatory compliance. Managers are encouraged to allocate budgets for digital integration, prioritize change management for technology adoption and invest in a skilled workforce. The adoption and management of DTs are highlighted to enhance resilience. Overall, the paper guides pharmaceutical organizations in navigating the complexities of the VUCA environment, ensuring the quality and safety of products through a multifaceted approach that combines advanced technologies with sustainability practices, supply chain diversification and collaborative ecosystems. Social implications The research addresses VUCA challenges, including volatility, uncertainty, complexity and ambiguity in pharmaceutical manufacturing. It emphasizes societal benefits such as uninterrupted drug supply, environmental responsibility through sustainable practices and enhanced collaboration among stakeholders. By leveraging digital technologies and resilience strategies, the study highlights the pharmaceutical sector’s pivotal role in managing health crises and ensuring patient safety. Originality/value This paper offers substantial originality and value by presenting a comprehensive framework for bolstering resilience in pharmaceutical manufacturing within the VUCA environment. The integration of advanced digital technologies, notably DTs, is explored in-depth, providing novel insights into their practical application. The “seizing, sensing and transforming” concept contributes a nuanced approach, considering both technological and human dimensions. This paper addresses the gaps in current literature by combining diverse elements such as Industry 4.0, risk assessment, sustainability practices and collaborative ecosystems. Its practical implications for managers and detailed exploration of research directions add tangible value, guiding future endeavors in enhancing pharmaceutical industry resilience.

ABSTRACT: Digital transformation (DT) is the use and integration of digital technologies in all areas of an organization, leading to profound changes in its activities, operations and value creation for customers. It has become a matter of survival for organizations across all sectors, geographies and sizes. Despite its widespread adoption, DT success is not achieved by investing in technology alone; it is necessary to analyze the factors that influence success and understand why some companies gain a competitive advantage while others fail. This study examines three key factors of DT: business model innovation, digital technology integration and digital talent management, and their relationship to performance. In addition, we examine the environment in which each organization operates, considering the technological intensity of the sector as a potential moderating factor between these factors and performance. The study focuses on Spanish manufacturing companies, using data from the ESEE. By analyzing a panel data set of 9215 observations between 2011 and 2017, we provide evidence that the technological intensity of the sector significantly affects the relationship between business model innovation, digital technology integration, the development of new competencies and performance. The study shows that companies in medium- and low-tech sectors can benefit more quickly from investments aimed at business model innovation, digital technology integration and the development of new competencies, and achieve better short-term results compared to companies in high-tech sectors. These results suggest that, despite their limited investment in R&D, companies in medium- and low-tech sectors have resources and capabilities that compensate for their innovation activities.ABSTRACT: Digital transformation (DT) is the use and integration of digital technologies in all areas of an organization, leading to profound changes in its activities, operations and value creation for customers. It has become a matter of survival for organizations across all sectors, geographies and sizes. Despite its widespread adoption, DT success is not achieved by investing in technology alone; it is necessary to analyze the factors that influence success and understand why some companies gain a competitive advantage while others fail. This study examines three key factors of DT: business model innovation, digital technology integration and digital talent management, and their relationship to performance. In addition, we examine the environment in which each organization operates, considering the technological intensity of the sector as a potential moderating factor between these factors and performance. The study focuses on Spanish manufacturing companies, using data from the ESEE. By analyzing a panel data set of 9215 observations between 2011 and 2017, we provide evidence that the technological intensity of the sector significantly affects the relationship between business model innovation, digital technology integration, the development of new competencies and performance. The study shows that companies in medium- and low-tech sectors can benefit more quickly from investments aimed at business model innovation, digital technology integration and the development of new competencies, and achieve better short-term results compared to companies in high-tech sectors. These results suggest that, despite their limited investment in R&D, companies in medium- and low-tech sectors have resources and capabilities that compensate for their innovation activities. Keywords: Digital transformation; performance of Spanish manufacturing firms; business model innovation; digital technology integration; digital talent management; industry’s technological intensity. Keywords: Digital transformation; performance of Spanish manufacturing firms; business model innovation; digital technology integration; digital talent management; industry’s technological intensity.

This study determined the motivation, barriers, and self-efficacy on digital technology of the nurse educators in the selected HEIs in CALABARZON, Philippines. Varied aspects of socio-cultural, training and professional development, attitude, leadership and administration, and pedagogy influenced the motivation in digital technology among nurse educators. On the other hand, lack of internet service, requiring more time to fully integrate technology in teaching, lack of adequate and necessary training, unclear implication of technology in professional practice, and lack of competence in adopting technology hindered their digital technology integration. Self-efficacy is facilitated by easy access to resources from the online library, the capability to meet deadlines, the capacity to efficiently learn to use a new type of digital technology, and being able to carry out their ethico-legal responsibilities regarding their role as teachers. Motivation and barriers are interrelated variables that influence digital technology use and integration among nurse educators. Barriers and self-efficacy have a high positive relationship that when self-efficacy is low, a reduction of barriers is also noted. Thus, nurse educators must be provided with continued support and training as they adapt to the education landscape and as they embrace the instructional challenges brought about by digital technology in the 21st century classroom.

This thesis provides new directions in the impedance spectroscopy, making it an interesting investigation technique for emerging smart sensors. Modern technologies increasingly require sensors capable of giving accurate measurements extracted among a lot of undesired surrounding information while maintaining low power consumptions. In this scenario, the main focuses of this thesis are: 1) developing an accurate complex impedance system, 2) extracting the augmented information using multivariate statistical analysis and 3) implementing IS-based systems with low power consumptions. The first project shows the design of a miniaturized, low power and accurate vector analyser for multi-parameter measurements in real-time. It is a versatile platform well-suited to be interfaced with various impedance-based sensors. The vector analyser, based on an accurate application specific integrated circuit and a digital interface, has been statistically characterized in order to evaluate accuracy and resolution. The validation of the entire system was performing on two real-time biomedical applications. The second project concerns the combination of powerful statistical methods inside moisture content sensors. The multivariate statistical approaches boost the prediction capability of the sensors exploiting the impedance mismatch between a transmitting and reflecting excitation on a soil. Two probe systems have been manufactured and associated with linear and non-linear models for being tested on three soil types. The third project shows a low-power implementation of an impedance sensor based on a digital random excitation. The entire system is almost digital, made up by an ultra-low power platform with the aim to become a wearable device. In future developments, these new investigated directions can be simultaneously applied in the design of IS based sensors which extract the desired information with high accuracy and reduced power budget. The potential of such improved system can be employed in a lot of smart sensors, involving electrochemical, environmental, food, biological applications and wearable devices.

Utilizing wearable technology in sport allows for the collection of motor behavior data during task engagement. This data can be assessed in real-time or retrospectively. Although enriching the scope of performance data, the consequences of wearable technology on the athlete-user, specifically the cognitive effects, has not been fully investigated, hence the purpose of this study.
\n This qualitative study examines the cognitions of 57 professional baseball players who wore eye tracking technology whilst engaged in batting practice. Their verbal self-reports were framed by temporal context: before-during-after task. Three themes emerged during the pre-task segment: social appearance anxiety, claimed self-handicapping, and curiosity. During the task of batting, verbal behavior contained motivational and instructional overt self-talk while claimed self-handicapping was sustained. The final, post-performance segment was marked by the re-emergence of curiosity from the pre-task period as well as self-evaluation/appraisal.
\n Given the participants were professional athletes, their performance has greater career implications than amateur competitors. Nonetheless, the verbal behavior elicited while wearing eye tracking technology indicates an awareness of the equipment by the user. This study found cognitive effects from wearable technology; more research is required to under-stand the scope and nature of those effects on cognitive and motor behaviors.

Aims: This review aims to analyze the impact of advancements in wearable technology and digital health solutions on health monitoring. The study focuses on how these innovations have improved the accuracy of health data collection, expanded access to medical monitoring, and strengthened patient engagement in self-care. Methods: A comprehensive literature review was conducted using publicly available databases, including PubMed, NEJM and Google Scholar, using articles available in English. Studies focusing on wearable health technology, its applications in chronic disease management, and its integration into healthcare systems were analyzed. Results: Wearable health technology has significantly enhanced real-time patient monitoring, enabling earlier detection of health conditions and more personalized treatment strategies. Devices such as smart watches, ECG monitors, and continuous glucose monitors have improved disease management and patient compliance. However, challenges related to data security, device interoperability, and patient adherences remain prevalent. Conclusion: Wearable health technology is transforming healthcare by providing continuous, real-time health monitoring and facilitating early intervention. While its potential is vast, addressing challenges such as data privacy and integration with existing medical systems is crucial for maximizing its benefits. Wearable health technologies are increasingly integrated into medical practice, offering new opportunities for continuous patient monitoring, early disease detection, and personalized treatment.

IT-experienced executives and digital-physical integration: An internal capabilities perspective

There is a need for illuminated cycle clothing that is comfortable and safe when cycling, and stylish to wear during other activities. It is particularly challenging to integrate lighting within textiles without compromising the drape and comfort of the textile structure. A team of electronics, textiles and fashion specialists was formed to design and make an illuminated jacket for use by cyclists. The jacket incorporates bespoke woven panels that integrate electronic yarns within the pattern. These were designed and made for this project, with fluorescent and retroreflective yarns also included in the weave. LEDs integrated within the electronic yarns illuminate the elbows of the jacket, without causing constraint or adding excess volume. The movement of the jacket elbows during cycling widens the body outline and makes the lighting eye-catching. The collaboration between electronics and textiles experts overcame challenges including development of electrical circuitry designed specifically to fit into the jacket unobtrusively, without interfering with movement or rucksack straps. Electrical connections were required between the electronic yarns assimilated within the weave. Standard, rigid solder joints would have been difficult to form without damaging the cloth and would have been liable to breakage within the garment structure, so embroidery techniques were used to create flexible, conductive connections. The illuminated jacket provides a working prototype, demonstrating the potential for further collaborative ventures in which electronics are integrated into garments that are stylish, functional and ‘wearable’. Further interdisciplinary research will include the development of additional wearable prototypes that enhance safety and wellbeing, whilst addressing the recycling of the textiles and garments, including the safe separation and disposal of electronic yarn and other components that provide electrical functionality.

Wearable smart devices have gradually become indispensable devices in people’s lives. Their security and privacy have gained increasing popularity among the public due to their ability to monitor and record various aspects of users’ daily activities and health data. These devices maintain a wireless connection with mobile phones through periodic signal transmissions, which can be intercepted and analyzed by external observers. While these signal packets contain valuable information about the device owner, the identity of the actual user remains unknown. In this study, we propose two approaches to link wearable smart devices with users’ mobile phones, which serve as electronic identities, to enable novel applications such as multi-device authentication and user-device graph construction for targeted advertising. To establish this linkage, we propose two approaches: a passive-sniffing-based linking approach and an active-interference-based linking approach, which solve the problem of sniffing Bluetooth Low Energy broadcast packets in two stages of Bluetooth Low Energy communication. Through experiments conducted across three scenarios, we demonstrate that seven wearable devices can be successfully linked with an accuracy rate exceeding 80%, with accuracy rates approaching 100% when a device is recorded more than 11 times. Additionally, we find that four wearable devices can be linked via an active-interference-based linking approach with an accuracy rate exceeding 70%. Our results highlight the potential of wearable devices and mobile phones as a means of establishing user identities and enabling the development of more sophisticated applications in the field of wearable technology.

Background New wearable sensor networks together with smartphone applications are being examined and tested for their potential to monitor and manage chronic liver disease (CLD) in type 2 diabetic patients. To develop methods for analyzes and monitor of map the intersection(s) of hepatology data in relation to CLD via wearable technology (MI band and Yu band). To study effects of daily life routine activities on data by wearable devices that can obtain real-time CLD data, help technologists understand medical aspects, and clinicians to understand technological processes them and provide assistance based on pre-determined specifications in CLD in type 2 diabetic patients in New Delhi, India. Methods Total of 106 CLD with type 2 diabetes patients were taken as the subject with an equal ratio of male and female. Wearable monitoring devices were put on the wrist of CLD patients for 30 days and a questionnaire was filled out by each patient. Both diabetes and cardiovascular disease, in turn, are known as important factors for developing CLD and aggravation toward once end-stage liver disease. In all subjects, blood glucose was measured on a daily basis with day to day data of their monitoring of step count (deep sleep, light sleep, wake up time), blood pressure, calorie burnt, insulin dose, motion time i.e., every time when your body was in motion, sleep monitoring, monitoring heart rate, cardiac arrhythmias to know daily routines and recording them for health purpose. Results Present results showed that both wearable device readings showed there was a normal heart rate, more calorie burnt with better control of sugar control and average good sleep count in more physically workout, include walking in CLD patients compared to less physically workout CLD patients, identified by professional physiotherapists. Both device readings showed that after changing lifestyle routine among less physically active CLD patients, their post- CLD events normalize with less requirement of medicine and insulin injection dose. Conclusions With this study we show that, by using, these wearable devices ensured online assistive feedback for CLD patients with type 2 diabetes is possible with their health awareness, exercising and motivate further studies.

IVDs constitute one of the major mainstays in today’s healthcare system. The utilization of advanced technologies for disease diagnosis can improve patient outcomes and aid in monitoring and treatment of the disease. The developments of AI tools can aid in maximizing patient care with multiple chronic conditions (MCC) by envisaging drug receptivity, adherence and interactions, while using data repositories to provide personalized medicine and care. The POCT can aid in rapid diagnosis which can be helpful for timely management of the disease. The use of non-invasive liquid biopsy helps in the detection of a broader range of cancers and other diseases at earlier stages. Moreover, it can support in detection of tumor recurrence and real-time monitoring of tumor dynamics and treatment response by recognizing specific markers in body fluids. Integration of digital technologies into healthcare platforms has several advantages. Electronic Health Records (EHRs), telemedicine, mobile health apps (mHealth), wearable devices, Laboratory Information Management System (LIMS) are some of the examples of cutting-edge digital technologies. Block chain technology can help in clinical trial management. Genomic medicine can be potentially useful in diagnosing rare disease genetic conditions, and many types of cancer. These futuristic prospects seem to have huge scope of technology based diagnosis thereby providing accurate results with small TATs aiding in timely and correct clinical decisions by HCPs for the patients.

Interacting with the Web of Things

This study proposes a new educational assessment framework to realize the organic integration of traditional assessment methods and digital technology. The model builds a three-dimensional assessment system by integrating dynamic data flow and educational big data. Considering the limitation of traditional assessment methods relying on periodic summary, a continuous dynamic feedback mechanism and a personalized learning tracking module are innovatively introduced. The technical program deeply integrates the educational theoretical system and intelligent algorithm technology to establish a panoramic assessment model in multiple dimensions such as academic development, class participation, and learning emotion. The system integrates classroom recording data, online assessment results, learning behavior logs, and other multi-source information to form a holographic portrait of learners' growth. In the research process, real teaching areas are selected to conduct technical verification. Experimental data show that the framework can effectively capture the dynamic characteristics of the learning process and provide real-time decision support for adapting teaching strategies. The technology optimization direction focuses on fine-tuning the granularity of data acquisition and explores the possibility of integrating new data inputs such as wearable devices. The practical application of this evaluation framework marks an important breakthrough in the direction of an intelligent and real-time education quality monitoring system.

ABSTRACTThe growing demand for self‐powered wearable electronic devices in healthcare, fitness, and entertainment has driven significant advancements in energy harvesting technologies. This review explores the latest progress in energy harvesting mechanisms that enable sustainable and autonomous wearable devices, with a particular emphasis on the role of polymers in their development. Polymers offer a unique combination of mechanical flexibility, biocompatibility, and lightweight properties, making them ideal for wearable applications. The review systematically categorizes the major energy harvesting technologies into three primary mechanisms: thermoelectric generators (TEGs), piezoelectric energy harvesters (PEHs), and triboelectric nanogenerators (TENGs). Each section provides an in‐depth discussion of the working principles, material innovations, fabrication techniques, and applications of these energy harvesting technologies in wearable systems. Beyond the fundamental mechanisms, the review discusses hybrid energy harvesting systems that integrate multiple energy sources to maximize power generation and ensure continuous device operation. The role of energy storage technologies, such as flexible supercapacitors and micro‐batteries, is also highlighted to address the intermittency challenges of ambient energy sources. Despite significant progress, challenges remain in improving energy conversion efficiency, enhancing device durability, and optimizing system integration for real‐world applications. The review identifies key research directions for overcoming these challenges, including advanced materials engineering, miniaturization techniques, and artificial intelligence‐driven energy management strategies. The findings presented in this review provide valuable insights into the development of next‐generation self‐powered wearable devices, paving the way for sustainable and efficient wearable electronics that seamlessly integrate into daily life.