Context: Sensor base data is being used for many purposes in designing various memory aid systems for cognitive impaired people. Different memory aids or reminder systems are based on various technologies such as NFC, accelerometer, GPS and gyroscope. Smart phones are equipped with such sensors and can be used for assistance of persons. In this study we use smart phone sensors in order to design a context aware reminder system to assist cognitive impaired people. Objectives: Different reminder systems, needs for such systems, technologies and models used to build a reminder system are identified in this research work. Ultimate goal of the study is to assist cognitive people in their daily life activities, using available embedded technologies of smart phones. Following objectives were set to achieve the goal of the thesis work: • What are reminder systems and why do we need such systems? • What are the different kinds of technologies reported in literature for reminder systems? • What are the issues encountered by cognitive impaired/elderly people while performing their daily life activities? • How to design and implement context aware reminder system using Smartphone embedded sensors? Methods: Mix method approach is used to carry out this study. Literature review is conducted based on the notion of systematic review. Data is collected through survey and interviews, conducted in south Sweden municipality, to analyze and indentify daily life issues and problems of cognitive people. Experiments are performed in real environment to test and verify our application. We evaluate the performance of activity recognition algorithm, implemented in the application, using Weka. Results: Various reminder systems, their needs and underlined technologies are identified and reported. Activities of daily living and issues addressed by these reminder systems are also identified. Survey and interviews help us to identify issues and problems faced by cognitive impaired/elderly while performing their daily life activities. For example, we find out that cognitive people not only forget their daily life activities but also during performing these activities. Conclusions: Many proposed models in literature are related to each other and use similar sensor based data from various technologies. Based on literature review, survey and interviews we have concluded that context based reminder system is essential for cognitive disabled people. It leads us to design a context based reminder system for android based smart phones. The preliminary tests help us to verify our model but there is absolute need for further empirical verification and validation.

Problem: A Major challenge for healthcare providers is the non-adherence of patients to prescrip- tions. One important area is hypertension treatment through medication. A treatment often starts with multiple adjustment cycles of medication type or dosage, which are based on regular at-home blood pressure measurements. Patients therefore need to adhere to regular medication intake and blood pressure measurements. Research Aim: The project first explored whether or not it is possible to develop a medication reminder system that checks patient adherence based on vital parameters. The project goal was adapted to the design and development of a reminder and data logging system for hypertension patients, based on the following research questions: 1) What are functional and non- functional requirements for the proposed artefact? 2) How can these requirements be implemented? Method: The project makes use of Design Science Research to create the system. The problem and requirement explication for the new artefact was achieved by working closely with a general prac- titioner who deals with hypertension patients. The artefact was evaluated by presenting it ex-post to a focus group of a hypertension patient, developers and founders in digital health. Results: The results of expert interviews concluded that the initial project aim is not feasible due to continuous vital monitoring being invasive and intrusive, lack of applicability for health conditions and medica- tions and other potential negative consequences. These insights led to the new research aim. The results address the question: ”What are functional and non-functional requirements for the proposed artefact?”. The envisioned product is a cross-platform application, illustrating the frequent medica- tion adjustments for hypertension patients. The treating doctor should configure all patient-specific parameters and the app should guide patients through daily tasks like measurements and medication intake. The patient should also be reminded of their tasks. The app should record, display, and export data for the doctor’s review, and ensure easy input of measurements. Future remote data exchange capabilities via servers were also considered. To address the research question ”How can these requirements be implemented?”, the researcher developed a cross-platform mobile application for iOS and Android with .NET Multi-Platform App UI (MAUI) that implements the desired features. A concept for remote data exchange and a system for scanning measured values of blood pressure devices were developed. The evaluation partially validated the problem area and discussed future implementations, such as remote data exchange, usage of patient data for research and adoption to other medication. The perceived high usability of the application was emphasized. Conclusions: The researcher concludes that the developed artefact addresses a relevant problem and extends existing solutions in the problem space. It is acknowledged that future research has to be conducted to prove the effectiveness of the tool as well as assess its usability and accuracy. Difficulties for accepting the artefact in real life settings are discussed.

Context. Reminder system offers flexibility in daily life activities and assists to be independent. The reminder system not only helps reminding daily life activities, but also serves to a great extent for the people who deal with health care issues. For example, a health supervisor who monitors people with different health related problems like people with disabilities or mild dementia. Traditional reminders which are based on a set of defined activities are not enough to address the necessity in a wider context. To make the reminder more flexible, the user’s current activities or contexts are needed to be considered. To recognize user’s current activity, different types of sensors can be used. These sensors are available in Smartphone which can assist in building a more contextual reminder system. Objectives. To make a reminder context based, it is important to identify the context and also user’s activities are needed to be recognized in a particular moment. Keeping this notion in mind, this research aims to understand the relevant context and activities, identify an effective way to recognize user’s three different activities (drinking, walking and jogging) using Smartphone sensors (accelerometer and gyroscope) and propose a model to use the properties of the identification of the activity recognition. Methods. This research combined a survey and interview with an exploratory Smartphone sensor experiment to recognize user’s activity. An online survey was conducted with 29 participants and interviews were held in cooperation with the Karlskrona Municipality. Four elderly people participated in the interview. For the experiment, three different user activity data were collected using Smartphone sensors and analyzed to identify the pattern for different activities. Moreover, a model is proposed to exploit the properties of the activity pattern. The performance of the proposed model was evaluated using machine learning tool, WEKA. Results. Survey and interviews helped to understand the important activities of daily living which can be considered to design the reminder system, how and when it should be used. For instance, most of the participants in the survey are used to using some sort of reminder system, most of them use a Smartphone, and one of the most important tasks they forget is to take their medicine. These findings helped in experiment. However, from the experiment, different patterns have been observed for three different activities. For walking and jogging, the pattern is discrete. On the other hand, for drinking activity, the pattern is complex and sometimes can overlap with other activities or can get noisy. Conclusions. Survey, interviews and the background study provided a set of evidences fostering reminder system based on users’ activity is essential in daily life. A large number of Smartphone users promoted this research to select a Smartphone based on sensors to identify users’ activity which aims to develop an activity based reminder system. The study was to identify the data pattern by applying some simple mathematical calculations in recorded Smartphone sensors (accelerometer and gyroscope) data. The approach evaluated with 99% accuracy in the experimental data. However, the study concluded by proposing a model to use the properties of the identification of the activities and developing a prototype of a reminder system. This study performed preliminary tests on the model, but there is a need for further empirical validation and verification of the model. / +46707560843