The purpose of this study was to gain a deeper understanding of the patient’s perspective regarding social interactions in video healthcare meetings. Social presence theory was used in the context of how video calls can result in vital aspects of social interactions disappearing and how that can affect the outcome of a doctor consultation in contrast to physical meetings. A qualitative method with semi-structured interviews was applied to this study. This study included 7 participants with similar age range from 26-36 years old including both genders. This study resulted in many different views and perspectives whereas some participants found it harder to communicate virtually whereas others did not think that social interactions was not even an important factor. The conclusion that could be made from this study is that virtual healthcare meetings are good depending on which context they are used for. Furthermore, the doctor cannot always get the full picture because the camera creates a psychological distance which makes it harder for the doctor to observe as much as he/she can in a physical setting which can lead to many signals and cues missing out.

Increase in population and limited resources have created a growing demand for a futuristic living environment where technology enables the efficient utilization and management of resources in order to increase quality of life. One characteristic of such a society, which is often referred to as a ‘Smart City’, is that the people are well informed about their physiological being as well as the environment around them, which makes them better equipped to handle crisis situations. There is a need, therefore, to develop wireless sensors which can provide early warnings and feedback during calamities such as floods, fires, and industrial leaks, and provide remote health care facilities. For these situations, low-cost sensor nodes with small form factors are required. For this purpose, the use of a low-cost, mass manufacturing technique such as inkjet printing can be beneficial due to its digitally controlled additive nature of depositing material on a variety of substrates. Inkjet printing can permit economical use of material on cheap flexible substrates that allows for the development of miniaturized freeform electronics. This thesis describes how low-cost, inkjet-printed, wireless sensors have been developed for real-time monitoring applications. A 3D buoyant mobile wireless sensor node has been demonstrated that can provide early warnings as well as real-time data for flood monitoring. This disposable paper-based module can communicate while floating in water up to a distance of 50 m, regardless of its orientation in the water. Moreover, fully inkjet-printed sensors have been developed to monitor temperature, humidity and gas levels for wireless environmental monitoring. The sensors are integrated and packaged using 3D inkjet printing technology. Finally, in order to demonstrate the benefits of such wireless sensor systems for health care applications, a low-cost, wearable, wireless sensing system has been developed for chronic wound monitoring. The system called ‘Smart Bandage’ can provide early warnings and long term data for medical diagnoses. These demonstrations show that inkjet printing can enable the development of low-cost wireless sensors that can be dispersed in the environment or worn on the human body to enable an internet of things (IoT), which can facilitate better and safer living.

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The delivery of quality healthcare to all citizens at reasonable costs is an important challenge. With the increase in the aging population, the costs of managing chronic diseases increase. Today, healthcare services tend to shift from recovery to prevention. Remote healthcare monitoring is crucial for prevention and monitoring of chronic diseases since they require continuous and long-term monitoring. The advances in networking, mobile communications and medical device technologies offer a great potential to realize remote healthcare monitoring. However, seamless integration of multi-modal medical devices to the existing healthcare information systems is necessary for the automated use of medical device observations in related applications. The thesis addresses the automatic acquisition and use of multi-modal medical device observations in healthcare information systems. The interoperability of medical devices with healthcare information systems requires both physical connectivity and application level interoperability. Therefore, the thesis concentrates on both the medical device domain and the interoperability efforts on the existing healthcare information systems. It provides an interoperability solution based on ISO/IEEE 11073 and HL7 standards. This work is also realized the automatic acquisition and use of multi-modal medical device observations in an intelligent healthcare monitoring and decision support system which is developed as a part of the IST-027074 SAPHIRE project funded by the European Commission.

The increasing life expectancy of an aging population has caused a higher demand for healthcare services, highlighting a shortage within the healthcare system due to insufficient projected growth of healthcare personnel. One solution to this issue is the utilization of the Internet of Medical Things (IoMT). This study aims to describe the general acceptance level amongst healthcare recipients of adopting IoMT in Swedish remote healthcare and how the acceptance level differs amongst different age groups depending on the application of IoMT. Acceptance and implementation of IoMT in remote healthcare are discussed, with an emphasis on factors such as user-friendliness and practical hardware design. In this study, a digital survey was conducted with 103 respondents, which demonstrated that the majority were positive about using IoMT for monitoring and treating health conditions remotely. Although awareness of security risks exists, respondents generally expressed a low number of concerns regarding unauthorized access to information and modification of IoMT devices in general. The study's conclusion highlights the notable acceptance of IoMT in remote healthcare in Sweden. The results indicate network-connected devices are integrated into people's daily lives, and user-friendliness and cybersecurity influence the adoption of IoMT. Older age groups demonstrated less concern about cybersecurity than younger age groups. When analysing specific applications, the results show some age-related differences in acceptance, which also varied depending on the application, particularly when comparing more life-critical devices such as IoMT pacemakers with IoMT fall detectors. / Den ökande livslängden hos en ökande befolkning har skapat ett ökat vårdbehov och detta har påvisat en brist inom sjukvården då den förväntade utvecklingen av sjukvårdspersonal är otillräcklig. En lösning på detta är användandet av Internet of Medical Things (IoMT) och denna studie har som syfte att beskriva den allmänna acceptansnivån hos vårdtagare för användandet av IoMT inom den svenska distansvården samt hur acceptansnivån skiljer sig för olika åldrar beroende på tillämpning av IoMT. Acceptans och implementering av IoMT i distanssjukvården diskuteras, och faktorer som användarvänlighet och praktisk hårdvarudesign betonas. I denna studie utfördes en digital enkätundersökning innehållande 103 respondenter som visade att majoriteten var positiva till att använda IoMT för att övervaka och behandla hälsotillstånd på distans. Även om medvetenheten om säkerhetsrisker finns, var respondenternas oro för obehörig åtkomst till information samt modifiering av IoMT-utrustning generellt låg. Studiens slutsats framhäver att distansvård med IoMT har en hög acceptans i Sverige. Resultaten indikerar att nätverksanslutna enheter är integrerade i människors vardag och att användarvänlighet samt cybersäkerhet påverkar användningen av IoMT. Äldre åldersgrupper visade mindre oro för cybersäkerheten än yngre åldersgrupper. Vid analys av specifika tillämpningar visar resultaten att det finns vissa åldersrelaterade skillnader i acceptans, vilka också varierade beroende på tillämpning, särskilt i jämförelse med mer livskritiska enheter såsom IoMT-pacemakers i jämförelse med IoMT-falldetektorer.

Global rise in life expectancy has resulted in an increased demand for affordable healthcare and monitoring services. The advent of miniature and low–power sensor technologies coupled with the emergence of the Internet–of–Things has paved the way towards affordable health monitoring tools in wearable platforms. However, ensuring power–efficient operation, data accuracy and user comfort are critical for such wearable systems. This thesis focuses on the development of accurate and computationally efficient algorithms and low–cost, unobtrusive devices with potential predictive capability for monitoring mobility and cardiac health in a wearable platform. A three–stage complementary filter–based approach is developed to realize a computationally efficient method to estimate sensor orientation in real–time. A gradient descent–based approach is used to estimate the gyroscope integration drift, which is subsequently subtracted from the integrated gyroscope data to get the sensor orientation. This predominantly gyroscope–based orientation estimation approach is least affected by external acceleration and magnetic disturbances. A two–stage complementary filter–based efficient sensor fusion algorithm is developed for real–time monitoring of lower–limb joints that estimates the IMU inclinations in the first stage and uses a gradient descent–based approach in the second stage to estimate the joint angles. The proposed method estimates joint angles primarily from the gyroscope measurements without incorporating the magnetic field measurement, rendering the estimated angles least affected by any external acceleration and insensitive to magnetic disturbances. An IMU–based simple, low–cost and computationally efficient gait–analyzer is developed to track the course of an individual's gait health in a continuous fashion. Continuous monitoring of gait patterns can potentially enable detecting musculoskeletal or neurodegenerative diseases at the early onset. The proposed gait analyzer identifies an anomalous gait with moderate to high accuracy by evaluating the gait features with respect to the baseline clusters corresponding to an individual’s healthy peer group. The adoption of a computationally efficient signal analysis technique renders the analyzer suitable for systems with limited processing capabilities. A flexible dry capacitive electrode and a wireless ECG monitoring system with automatic anomaly detection capability are developed. The flexible capacitive electrode reduces motion artifacts and enables sensing bio–potential over a dielectric material such as cotton cloth. The virtual ground of the electrode allows for obtaining single–lead ECG using two electrodes only. ECG measurements obtained over different types of textile materials and in presence of body movements show comparable performance to other reported ECG monitoring systems. An algorithm is developed separately as a potential extension of the software to realize automatic identification of Atrial Fibrillation from short single–lead ECGs. The association between human gait and cardiac activities is studied. The gait is measured using wearable IMUs and the cardiac activity is measured with a single–lead handheld ECG monitor. Some key cardiac parameters, such as heart rate and heart rate variability and physical parameters, such as age and BMI show good association with gait asymmetry and gait variation. These associations between gait and heart can be useful in realizing low–cost in–home personal monitoring tool for early detecting CVD–related changes in gait features before the CVD symptoms are manifested. / Thesis / Doctor of Philosophy (PhD) / Wearable health monitoring systems can be a viable solution to meet the increased demand for affordable healthcare and monitoring services. However, such systems need to be energy–efficient, accurate and ergonomic to enable long–term monitoring of health reliably while preserving user comfort. In this thesis, we develop efficient algorithms to obtain real–time estimates of on–body sensors' orientation, gait parameters such as stride length, and gait velocity and lower–limb joint angles. Furthermore, we develop a simple, low–cost and computationally efficient gait–analyzer using miniature and low–power inertial motion units to track the health of human gait in a continuous fashion. In addition, we design flexible, dry capacitive electrodes and use them to develop a portable single–lead electrocardiogram (ECG) device. The flexible design ensures better conformity of the electrode to the skin, resulting in better signal quality. The capacitive nature allows for obtaining ECG signals over insulating materials such as cloth, thereby potentially enabling a comfortable means of long–term cardiac health monitoring at home. Besides, we implement an automatic anomaly detection algorithm that detects Atrial Fibrillation with good accuracy from short single–lead ECGs. Finally, we investigate the association between gait and cardiac activities. We observe that some important cardiac signs, such as heart rate and heart rate variability and physical parameters, such as age and BMI show good association with gait asymmetry and gait variation.