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Monitoring fitness activities using a wearable device
Toman, Adam ; Trčka, Tomáš (referee) ; Tofel, Pavel (advisor)
Bachelor thesis deals with the issue of fitness tracking with wearable device. Theoretical part describes the historical development of wearable devices, the base theory behind fitness activities and resistence training and methods of using of wearable devices for classification and evaluation of these activities. Aim for the practical part of this thesis was to develop an algorithm able to classify and evaluate activities through chosen recorded metrics. Practical part is followed by overall result evaluation and discussion.
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Determining Stress Level from Heart Rate Monitoring
Hodulík, Hynek ; Strnadel, Josef (referee) ; Bidlo, Michal (advisor)
This thesis outlines the development of a prototype wearable embedded device intended for stress detection via physiological measurements utilizing an EKG sensor. Communication for the device is facilitated through Bluetooth LE. Accompanying the device is an algorithm designed to estimate stress levels locally based on collected heart rate variability data. Following a comparison of various methods, a multilayer perceptron was selected for stress detection. The proposed solution demonstrates an 85% accuracy rate in stress detection on WESAD dataset.
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Human behaviour monitoring system based on smartphone and bracelet data analysis
Mikulec, Marek ; Zvončák, Vojtěch (referee) ; Mekyska, Jiří (advisor)
There has been established new technological field using smart phones and wearable devices for medical research since the arrival of health 4.0. The main goal of this work is to design, implement and test new system for monitoring people´s behaviour using smart phone and wearable device. These smart compoments should oblige requirements of health~4.0. This work uses open source software AWARE Framework and data from Fitbit API. The final system enables gathering and sharing 36 measurable metrics from smart phone and wearable device. Furthermore it secures efective access to gathered data and puts particular emphasis on the security of the system. Finally the system was used to examine a patterns of REM (Rapid Eye Movement) sleep behaviour disorder.
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Intelligent Control Using Hand Gestures
Apjar, Martin ; Hyrš, Martin (referee) ; Šimek, Václav (advisor)
This work deals with a creation of the device suitable for capturing the gestures of the human´s hand, selection of suitable sensors, creation of service software and communication proposal. The device working is based on Arduino board with microprocessor from the company Atmel ATmega32u4. In the first part of the thesis a detailed search of the existing ways of solving the given problem was performed. The following sections are devoted to the design of my solution, the description of the fabrication of the model body and the description of the used materials. Further, the Thesis contains a description of all sensors and scanners and a detailed description of the supplied PCB. At the end we will find the program section where the control and sensor work is disassembled. The result of this work is a hand-held model and firmware.
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Electronic clinical study management system with artificial intelligence-based data processing capabilities
Mužný, Miroslav ; Mužík, Jan (advisor) ; Štěpánková, Olga (referee) ; Ngo, Phuong Dinh (referee)
An increasing amount of data are collected through wearable devices during ambulatory, and long-term monitoring of biological signals, adoption of persuasive technology and dynamics of clinical trials information sharing - all of that changes the possible clinical intervention. Moreover, more and more smartphone apps are hitting the market as they become a tool in daily life for many people around the globe. All of these applications are generating a tremendous amount of data, that is difficult to process using traditional methods, and asks for engagement of advanced methods of data processing. For recruiting patients, this calls for a shift from traditional methods of engaging patients to modern communication platforms such as social media, that are providing easy access to up- to-date information on an everyday basis. These factors make the clinical study progression demanding, in terms of unified participant management and processing of connected digital resources. Some clinical trials put a strong accent on remote sensing data and patient engagement through their smartphones. To facilitate this, a direct participant messaging, where the researchers give support, guidance and troubleshooting on a personal level using already adopted communication channels, needs to be implemented. Since the...
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Electronic clinical study management system with artificial intelligence-based data processing capabilities
Mužný, Miroslav ; Mužík, Jan (advisor) ; Štěpánková, Olga (referee) ; Ngo, Phuong Dinh (referee)
An increasing amount of data are collected through wearable devices during ambulatory, and long-term monitoring of biological signals, adoption of persuasive technology and dynamics of clinical trials information sharing - all of that changes the possible clinical intervention. Moreover, more and more smartphone apps are hitting the market as they become a tool in daily life for many people around the globe. All of these applications are generating a tremendous amount of data, that is difficult to process using traditional methods, and asks for engagement of advanced methods of data processing. For recruiting patients, this calls for a shift from traditional methods of engaging patients to modern communication platforms such as social media, that are providing easy access to up- to-date information on an everyday basis. These factors make the clinical study progression demanding, in terms of unified participant management and processing of connected digital resources. Some clinical trials put a strong accent on remote sensing data and patient engagement through their smartphones. To facilitate this, a direct participant messaging, where the researchers give support, guidance and troubleshooting on a personal level using already adopted communication channels, needs to be implemented. Since the...
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Human behaviour monitoring system based on smartphone and bracelet data analysis
Mikulec, Marek ; Zvončák, Vojtěch (referee) ; Mekyska, Jiří (advisor)
There has been established new technological field using smart phones and wearable devices for medical research since the arrival of health 4.0. The main goal of this work is to design, implement and test new system for monitoring people´s behaviour using smart phone and wearable device. These smart compoments should oblige requirements of health~4.0. This work uses open source software AWARE Framework and data from Fitbit API. The final system enables gathering and sharing 36 measurable metrics from smart phone and wearable device. Furthermore it secures efective access to gathered data and puts particular emphasis on the security of the system. Finally the system was used to examine a patterns of REM (Rapid Eye Movement) sleep behaviour disorder.
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Intelligent Control Using Hand Gestures
Apjar, Martin ; Hyrš, Martin (referee) ; Šimek, Václav (advisor)
This work deals with a creation of the device suitable for capturing the gestures of the human´s hand, selection of suitable sensors, creation of service software and communication proposal. The device working is based on Arduino board with microprocessor from the company Atmel ATmega32u4. In the first part of the thesis a detailed search of the existing ways of solving the given problem was performed. The following sections are devoted to the design of my solution, the description of the fabrication of the model body and the description of the used materials. Further, the Thesis contains a description of all sensors and scanners and a detailed description of the supplied PCB. At the end we will find the program section where the control and sensor work is disassembled. The result of this work is a hand-held model and firmware.
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