A WIoT is a wireless network of low-power sensing nodes placed on the human body. While operating, these networks routinely collect physiological signals to send to offsite medical professionals for review. In this manner, these networks support a concept known as pervasive healthcare in which patients can be continuously monitored and treated remotely. Given that these networks are used to guide medical treatment and depend on transmitting sensitive data, it is important to ensure that the communication channel remains secure. Symmetric pairwise cryptography is a traditional scheme that can be used to provide such security. The scheme functions by sharing a cryptographic key between a pair of sensors. Once shared, the key can then be used by both parties to encrypt and decrypt all future messages. To configure a WIoT to support the use of symmetric pairwise cryptography a key distribution protocol is required. Schemes for pre-deployment are often used to perform this distribution. These schemes usually require inserting key information into WIoT devices before they can be used in the network. Unfortunately, this need to manually configure WIoT devices can decrease their usability. In this thesis we propose and evaluate an alternative approach to key distribution that uses physiological signals derived from accelerometer and gyroscope sensors. The evaluation of our approach indicates that more study is required to determine techniques that will enable ballistocardiography-derived physiological signals to provide secure key distribution.

"A wireless wearable battery-operated pulse oximeter has been developed in our laboratory for field triage applications. The wearable pulse oximeter, which uses a forehead-mounted sensor to provide arterial oxygen saturation (SpO2) and heart rate (HR) information, would enable field medics to monitor vital physiological information following critical injuries, thereby helping to prioritize life saving medical interventions. This study was undertaken to investigate if accelerometry (ACC)-based adaptive noise cancellation (ANC) is effective in minimizing SpO2 and HR errors induced during jogging to simulate certain motion artifacts expected to occur in the field. Preliminary tests confirmed that processing the motion corrupted photoplethysmographic (PPG) signals by simple Least-Mean-Square (LMS) and Recursive Least-Squares (RLS) ANC algorithms can help to improve the signal-to-noise ratio of motion-corrupted PPG signals, thereby reducing SpO2 and HR errors during jogging. The study showed also that the degree of improvement depends on filter order. In addition, we found that it would be more feasible to implement an LMS adaptive filter within an embedded microcontroller environment since the LMS algorithm requires significantly less operations."

"Modern ultrasound scanners are portable and have become very useful for clinical diagnosis. However, they have limitations for field use purposes, primarily because they occupy both hands of the physician who performs the scanning. The goal of this thesis is to develop a wearable voice-controlled ultrasound scanner system that would enable the physician to provide a fast and efficient diagnosis. This is expected to become very useful for emergency and trauma applications. A commercially available ultrasound scanner system, Terason 2000, was chosen as the basis for development. This system consists of a laptop, a hardware unit containing the RF beamforming and signal processing chips and the ultrasound transducer. In its commercial version, the control of the ultrasound system is performed via a Graphical User Interface with a Windows-application look and feel. In the system we developed, a command and control speech recognition engine and a noise-canceling microphone are selected to control the scanner using voice commands. A mini-joystick is attached to the top of the ultrasound transducer for distance and area measurements and to perform zooming of the ultrasound images. An eye-wear viewer connected to the laptop enables the user to view the ultrasound images directly. Power management features are incorporated into the ultrasound system in order to conserve the battery power. A wireless connection is set up with a remote laptop to enable real-time transmission of wireless images. The result is a truly untethered, voice-controlled, ultrasound system enclosed in a backpack and monitored by the eye-wear viewer. (In the second generation of this system, the laptop is replaced by an embedded PC and is incorporated into a photographer’s vest). The voice-controlled system has to be made reliable under various forms of background noise. Three command and control speech recognition systems were selected and their recognition performances were determined under different types and levels of ambient noise. The variation of recognition rates was also analyzed over 6 different speakers. A detailed testing was also conducted to identify the ideal combination of a microphone and speech recognition engine suitable for the ultrasound scanner system. Six different microphones, each with their own unique methods of implementing noise cancellation features, were chosen as candidates for this analysis. The testing was conducted by making recordings inside a highly reverberant acoustic noisy chamber, and the recordings were fed to the automatic speech recognition engines offline for performance evaluation. The speech recognition engine and microphone selected as a result of this extensive testing were then incorporated into the wearable ultrasound scanner system. This thesis also discusses the implementation of the human-speech interface, which also plays a major role in the effectiveness of the voice-controlled ultrasound scanner system."

This research explores a new way of enhancing audience experience in film entertainment, presenting the design and implementation of a wearable prototype system that uses haptic sensations to intensify moods in lm music. The aim of this work is to enrich the musical experience of film audiences and might also have implications on the hearing-impaired, providing them with a new enhanced emotional experience while watching a movie. Although there has been previous work into music displays of a visual and haptic nature, and on the importance of music in film, there is no documented research on musical enhancement experience in film entertainment. This work focuses on the mood conveyed by film music in order to understand what role it plays in creating the film experience, and also explores the possibility of enhancing those feelings through haptic sensations. Drawing on HCI and interaction design principles, the design of a piece of haptic wearable technology is proposed and used as the tool for user studies. This research contributes to the fields of: HCI, interaction design, user experience design, multimodal interaction, creative technology, wearable technology, haptics, entertainment technology and film music. This work also provides a set of design suggestions to aid future research and designers of haptic sensations for media enhancement. Proposed guidelines are based on a number of empirical findings that describe and explain aspects of audience emotional response to haptics, providing some first evidence that there is a correlation between vibrotactile stimuli (such as frequency and intensity) and perceived feelings.

Advances in wearable technologies are facilitating the understanding of human activities using first-person vision (FPV) for a wide range of assistive applications. In this thesis, we propose robust multiple motion features for human activity recognition from first-person videos. The proposed features encode discriminant characteristics from magnitude, direction and dynamics of motion estimated using optical flow. Moreover, we design novel virtual-inertial features from video, without using the actual inertial sensor, from the movement of intensity centroid across frames. Results on multiple datasets demonstrate that centroid-based inertial features improve the recognition performance of grid-based features. Moreover, we propose a multi-layer modelling framework that encodes hierarchical and temporal relationships among activities. The first layer operates on groups of features that effectively encode motion dynamics and temporal variations of intra-frame appearance descriptors of activities with a hierarchical topology. The second layer exploits the temporal context by weighting the outputs of the hierarchy during modelling. In addition, a post-decoding smoothing technique utilises decisions on past samples based on the confidence of the current sample. We validate the proposed framework with several classifiers, and the temporal modelling is shown to improve recognition performance. We also investigate the use of deep networks to simplify the feature engineering from firstperson videos. We propose a stacking of spectrograms to represent short-term global motions that contains a frequency-time representation of multiple motion components. This enables us to apply 2D convolutions to extract/learn motion features. We employ long short-term memory recurrent network to encode long-term temporal dependency among activities. Furthermore, we apply cross-domain knowledge transfer between inertial-based and vision-based approaches for egocentric activity recognition. We propose sparsity weighted combination of information from different motion modalities and/or streams. Results show that the proposed approach performs competitively with existing deep frameworks, moreover, with reduced complexity.

In recent years, due to the combination of technological advances in the fields ofmeasurement instrumentation, communications, home-health care and textile-technology thedevelopment of medical devices has shifted towards applications of personal healthcare.There are well known the available solutions for heart rate monitoring successfully providedby Polar and Numetrex. Furthermore new monitoring applications are also investigated. Amongthese non-invasive monitoring applications, it is possible to find several ones enable bymeasurements of Electrical Bioimpedance.Analog Devices has developed the AD5933 Impedance Network Analyzer which facilitatesto a large extent the design and implementation of Electrical Bioimpedance Spectrometers in amuch reduced space. Such small size allows the development of a fully wearable bioimpedancemeasurement.With the development of a Electrical Bioimpedance-enable wearable medical device in focusfor personal healthcare monitoring, in this project, the issue of power management has beentargeted and a battery-driven Electrical Bioimpedance Spectrometer based in the AD5933 hasbeen implemented. The resulting system has the possibility to operate with a Li-Po battery with apower autonomy over 17 hours.

In this thesis, a novel graphene (GN) based electrocardiogram (ECG) sensor is designed, constructed and tested to validate the concept of coating GN, which is a highly electrically conductive material, on Ag substrates of conventional electrodes. The background theory, design, experiments and results for the proposed GN-based ECG sensor are also presented. Due to the attractive electrical and physical characteristics of graphene, a new ECG sensor was investigated by coating GN onto itself. The main focus of this project was to examine the effect of GN on ECG monitoring and to compare its performance with conventional methods. A thorough investigation into GN synthesis on Ag substrate was conducted, which was accompanied by extensive simulation and experimentation. A GN-enabled ECG electrode was characterised by Raman spectroscopy, scanning electron microscopy along with electrical resistivity and conductivity measurements. The results obtained from the GN characteristic experimentation on Raman spectroscopy, detected a 2D peak in the GN-coated electrode, which was not observed with the conventional Ag/AgCl electrode. SEM characterisation also revealed that a GN coating smooths the surface of the electrode and hence, improves the skin-to-electrode contact. Furthermore, a comparison regarding the electrical conductivity calculation was made between the proposed GN-coated electrodes and conventional Ag/AgCl ones. The resistance values obtained were 212.4 Ω and 28.3 Ω for bare and GN-coated electrodes, respectively. That indicates that the electrical conductivity of GN-based electrodes is superior and hence, it is concluded that skin-electrode contact impedance can be lowered by their usage. Additional COMSOL simulation was carried out to observe the effect of an electrical field and surface charge density using GN-coated and conventional Ag/AgCl electrodes on a simplified human skin model. The results demonstrated the effectiveness of the addition of electrical field and surface charge capabilities and hence, coating GN on Ag substrates was validated through this simulation. This novel ECG electrode was tested with various types of electrodes on ten different subjects in order to analyse the obtained ECG signals. The experimental results clearly showed that the proposed GN-based electrode exhibits the best performance in terms of ECG signal quality, detection of critical waves of ECG morphology (P-wave, QRS complex and T-wave), signal-to-noise ratio (SNR) with 27.0 dB and skin-electrode contact impedance (65.82 kΩ at 20 Hz) when compared to those obtained by conventional a Ag/AgCl electrode. Moreover, this proposed GN-based ECG sensor was integrated with core body temperature (CBT) sensor in an ear-based device, which was designed and printed using 3D technology. Subsequently, a finger clipped photoplethysmography (PPG) sensor was integrated with the two-sensors in an Arduino based data acquisition system, which was placed on the subject's arm to enable a wearable multiple physiological measurement system. The physiological information of ECG and CBT was obtained from the ear of the subject, whilst the PPG signal was acquired from the finger. Furthermore, this multiple physiological signal was wirelessly transmitted to the smartphone to achieve continuous and real-time monitoring of physiological signals (ECG, CBT and PPG) on a dedicated app developed using the Java programming language. The proposed system has plenty of room for performance improvement and future development will make it adaptabadaptable, hence being more convenient for the users to implement other applications than at present.

The development of energy storage devices has represented a significant technological challenge for the past few years. Electrochemical double-layer capacitors (EDLCs), also named as supercapacitors, are a likely competitor for alternative energy storage because of their low-cost, high power density, and high fast charge/discharge rate. The recent development of EDLCs requires them to be lightweight and flexible. There are many fabrication techniques used to manufacture flexible EDLCs, and these methods can include pre-treatment to ensure more efficient penetration of activated carbon (AC) patterns onto the substrate, or those that utilise masks for the definitions of patterns on substrates. However, these methods are inconvenient for building cost-effective devices. Therefore, it was necessary to find a suitable process to reduce the steps of manufacture and to be able to print multiple materials uniformly. This research work describes the first use of a 3D printing technology to produce flexible EDLCs for energy storage. In this research work, the four essential elements for the EDLCs substrate, current collector, activated electrode, and gel electrolyte were investigated. The AC powder was milled by ball milling to optimise the paste deposition and the electrochemical performance. A flexible composite EDLC was designed and manufactured by 3D printing. The electrochemical performance of the flexible composite EDLCs was then examined. Being highly flexible is one of the critical demands for the recent development of EDLCs. Therefore, highly flexible EDLCs were designed and manufactured by only one single extrusion process. The 3D highly flexible EDLC maintains significant electrochemical performance under a mechanical bending test. To meet the power and energy requirements, the EDLCs were connected and tested in series and parallel circuits. A supercapacitor based on printed AC material displays an area specific capacitance of 1.48 F/cm2 at the scan rate of 20 mV/s. The coulombic efficiency for the flexible EDLC was found to be 59.91%, and the cycling stability was achieved to be 56% after 500 cycles. These findings indicate that 3D printing technology may be increasingly used to develop more sophisticated flexible wearable electronic devices.

In this modern landscape where families are spending increasing time living separately, due to parental separation, work travel, and illness, current communication technologies do not fully support the needs of intimate family communication in families with young children, aged two to nine. Prolonged separation, without intimate communication, can damage parent and child relationships, impacting on intimacy, bonding, and a child’s mental health and wellbeing. Care and play activities are the main methods used to build bonds between parent and child. These are hard to replicate with ubiquitous communication technologies when families are separated. Ubiquitous technology, such as the telephone, is easy to use but does not offer engaging ways for a child to interact. Skype (video call), has a higher potential for engagement due to its multimodal nature (audio and visual), therefore is more emotionally expressive. However, to ‘Skype’ someone, a child requires adult support, as the technology is more complex to use than that of a telephone. Thus, neither the telephone or Skype fully meet family needs for communication. Parental-child separation was looked at within parental separation, work travel and illness, to explain how intimacy can be achieved through technology mediated communication systems. Following a Participatory Action Research methodology, utilising methods such as co-design, co-creation, and participatory design, the research discusses five small-scale studies as well as the Trace project, which was the main study of this research. This research addresses communication issues between families through textile-based communication systems which enable intimacy and bonding. It highlights the importance of intimate communications and offers a list of preferred modes of communication for scattered families (multimodal disparate objects that allow for synchronous or asynchronous communications with either the same modes or different modes of input and output). It also outlines key methods for designing new technologies suitable for use in family research (inclusive methods such as co-design, co-creation and participatory design). A better understanding of the participant families’ emotional needs was achieved, by allowing them to become active participants at every stage of the design process (planning, acting, observing, and reflecting), thus producing considerate technologies for remote family communications.

People are increasingly recognizing how their health affects their quality of life, and health is most easily tracked through the use of wearable devices. The goal of this study is to detect and monitor human motion via gait analysis to provide information that will help people enhance their health. After reviewing a range of wearable health-tracking devices, the shoe has been chosen as one of the best device for observing human motion. / Most measurement systems currently used for motion and gait detection are disadvantaged in that they monitor and analyze motion in limited environments and not in real time. Hence, they cannot be used for long-term monitoring and detection. The design of a new, inexpensive, compact and lightweight shoe-integrated platform is elaborated in this thesis. The intelligent shoe system comprises a suite of sensors, a microprocessor board and a wireless communication module. This ideal platform requires no specialized equipment or lab setup, meaning data can be collected not only in the narrow confines of a research lab, but essentially anywhere, whether indoors or outdoors. / Our everyday lives are shaped by a wide variety of motions, some of which can cause injury. Injuries suffered due to falls account for a significant portion of accidents and immediate help should be provided. The intelligent shoe system offers an approach of detecting the user’s motion, especially the movement and direction of a fall. This study used principle component analysis (PCA) to decrease the number of sensors in the prototype (eight pairs) by half (four pairs), so as to reduce computational cost and enhance real-time performance. The resultant system can learn the patterns necessary to detect fall directions from abundant tilted-standing data instead of actual fall data. / Fatigue can result in an abnormal gait, making injury more probable. Hence, detecting fatigue is very important. Experiments have been conducted to determine the relationship between fatigue and gait, and the resultant data are used to analyze the relationship between force information and foot attitude. These findings can help a user detect fatigue and avoid injury. / People carry various kinds of loads in their daily lives, and long-term load-bearing activities can result in motion deformation. Another objective of this study is to determine a load-carrying approach that will decrease such deformation to a great extent. Resampling is used to partition the related data cycle by cycle. A support vector machine (SVM) is adopted to model a user’s normal walking gait and abnormal gaits without loads, which allows for the determination of whether a gait is normal when a load is carried. / To enhance overall health, exercise is commonly adopted, but many forms of exercise are dull. The proposed system’s shoe-computer interface not only helps people obtain detailed lower-body feedback, but can also be used to promote everyday exercise. People are analyzed while sitting for long periods in the workplace, and two interfaces are designed as a result: the shoe-keyboard, in which the feet are used to type words into a computer, and the shoe-write system, in which the foot is used like a hand to write on the ground, with the words displayed on the computer screen. Both of these applications use back-propagation (BP) networks to classify the motions involved. The shoe-keyboard is based on logical coding to map the motion-to-word relationship, and the shoe-write system incorporates an optical tracker to translate motion into information. / 人們現在越來越重視自己的生活質量，而健康方面是最為重要的。穿戴式設備是最好容易使用的檢測健康的設備。本文的目標是通過智能鞋，來檢測步態，對其進行分析和預測，已達到檢測和提高人們的健康水平的要求。 / 現在絕大多數的步態運動檢測系統都不是實時的且長時間工作的。在研究中，基於鞋子的智能系統被提出并得以實現，其具有便宜，緊湊，輕便等的優點。該系統包括壓力和加速度傳感器，處理芯片和無線傳輸模塊。這種設計將滿足日常步態信息的採集，并且把環境影響的因素放置最小，以達到室內室外都可長時間連續實時監測的要求。 / 在本論文中，對一系列日常生活的行為進行檢測和分類，尤其是最為危險的摔倒。本系統通過採用主成分分析，對已有的壓力傳感器進行的了分析，在保證了預測的準確性的前提下，將壓力傳感器由8對減少至4對，大大的降低了運算的次數，使得該系統實時性更好。同時本系統通過傾斜站立獲得的數據并應用于跌倒方向的檢測，並且有著良好的結果。 / 在本文中，對疲勞步態進行的分析，通過設計實驗，來區分不同疲勞程度下人們的步態。壓力信號較為明顯，同時加速度反映出每一步的劇烈程度。最終結果表明，壓力和加速度相輔相成，與疲勞程度的關係也很明顯，基於這種關係，本系統對疲勞程度進行了預測，通過壓力傳感器的信號，預測疲勞的程度，實驗結果也較為理想。 / 長時間的負責對身體的負擔很大，在本文中，著重的分析了在不同負重方式下，步態的變化，並且通過對比正常步態，採用支持向量機進行分類。在分類的過程中，通過重新採樣，將採集的數據轉變為一步為一組的數據，進行分類，最終得到的結果表明，平衡狀態下的負重是最好的。 / 對於健康而言，除了檢查受傷和疲勞，提升自身的身體素質也尤為重要。在本文中，介紹了兩種基於智能鞋的應用，在鍛煉下肢靈活度的同時，也避免了鍛煉的無聊。智能鞋鍵盤是通過腳踝的運動，基於一定的編碼方式，已達到在電腦上輸入文字的方式。智能鞋寫字系統是通過對下腳點的定位結合光電傳感器記錄位移，最終獲得文字輸入。應用BP神經網絡，對腳下點進行了分類，結合壓力傳感器和腿部建模，可以準確的區分30個的基本點的位置，從而獲得每筆的起點。最終完成寫字輸入。 / Tao, Yanbo. / Thesis Ph.D. Chinese University of Hong Kong 2014. / Includes bibliographical references (leaves 134-141). / Abstracts also in Chinese. / Title from PDF title page (viewed on 12, October, 2016). / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.