"Ultrasound imaging is a safe and powerful tool for providing detailed still and moving images of the human body. Most of today’s ultrasound systems are housed on a movable cart and designed for use within a clinical setting, such as in a hospital or doctor’s office. This configuration hinders its use in locations lacking controlled environments and stable power sources. Example locations include ambulances, disaster sights, war zones and rural medicine. A wearable ultrasound system, in the form of a vest worn by a sonographer, has been developed as a complete solution for performing untethered ultrasound examinations. The heart of the system is an enclosure containing an embedded computer running the Windows XP operating system, and a custom power supply. The power supply integrates a battery charger, a switching regulator, two linear regulators, a variable speed fan controller and a microcontroller providing an interface for monitoring and control to the embedded computer. Operation of the system is generally accomplished through the use of voice commands, but it may also be operated using a hand-held mouse. It is capable of operating for a full day, using two batteries contained in the vest. In addition, the system has the capability to wirelessly share live images with remote viewers in real-time, while also permitting full duplex voice communication. An integrated web-server also provides for the wireless retrieval of stored images, image loops and other information using a web-browser. "

Zugl.: Bremen, Univ., Diss., 2007

Diss. Universität Bremen, 2007.

Wearable computing systems have been researched and developed for several decades. With the advent of the head-mounted display, augmented and mediated reality systems became an important example of wearable computing. However, due to certain factors such as computational constraints, cost, obtrusiveness, practicality, and social acceptance, mediated reality systems have been leveraged in only very specific application domains and have yet to see mainstream adoption. This dissertation describes the research and development of a real-time mediated reality platform developed for modern mobile devices to provide a more reasonable transition in overcoming the mainstream adoption barrier of mediated reality systems. In particular, an outdoor navigational application that provides contextually-relevant information about a user’s surroundings is developed using the platform as a proof-of-concept for evaluation. In addition, the server infrastructure required to support the application is discussed, as well as the evaluation of a hybrid orientation tracking approach using sensors and computer vision.

Wearable computing systems have been researched and developed for several decades. With the advent of the head-mounted display, augmented and mediated reality systems became an important example of wearable computing. However, due to certain factors such as computational constraints, cost, obtrusiveness, practicality, and social acceptance, mediated reality systems have been leveraged in only very specific application domains and have yet to see mainstream adoption. This dissertation describes the research and development of a real-time mediated reality platform developed for modern mobile devices to provide a more reasonable transition in overcoming the mainstream adoption barrier of mediated reality systems. In particular, an outdoor navigational application that provides contextually-relevant information about a user’s surroundings is developed using the platform as a proof-of-concept for evaluation. In addition, the server infrastructure required to support the application is discussed, as well as the evaluation of a hybrid orientation tracking approach using sensors and computer vision.

In this thesis we develop and test a software algorithm for an electronic smart badge system. The smart badge system we have developed has the ability to figure out the interests of people who wear the badge by using time and position information collected by the badge. The badge can also present feedback to the wearer, so that users may be guided to people will similar interests and so may have more effective conversations. The smart badge system is based on an inference system which uses a Bayesian network. Evaluation of the system was challenging because there were no completed badges that could be used. To overcome this, we developed a simulation of crowd behaviour in a conference setting. We tuned the parameters of the model using several test situations and the final simulated behavior appeared realistic. Compared to other smart badge systems, our work is unique because it is able to enhance conversation by the real time inference of common ideas or interests of the conversion participants.

Wearable computers and e-textiles are increasingly prevalent in today's society. Motion capture is one of many potential applications for on-body electronic systems. Self-contained motion capture applications require information from sensors distributed throughout the body on a "smart" garment. Therefore, this thesis presents the design of a flexible hardware platform for e-textile motion capture applications. This thesis also presents software for one such application, namely, tracking the pose or relative position of body limbs. The accuracy of this solution is compared to an industrial optical motion capture system. The combined hardware and software design are successful at collecting and processing motion capture data in the context of an e-textile jumpsuit. / Master of Science

The goal of this project was to determine the feasibility of non-invasively monitoring the blood gases of construction workers for carbon monoxide exposure via pulse oximetry. In particular, this study sought to understand the impact of motion artifacts caused by the worker's activities and to determine if those activities would prevent the blood gas sensor from detecting the onset of carbon monoxide poisoning. This feasibility study was conducted using a blood oxygen sensor rather than a blood carbon monoxide sensor for several reasons. First, blood gas sensors that measure blood carbon monoxide are not readily available in suitable physical form factors. Second, sensors for blood oxygen and blood carbon monoxide operate on the same physical principles and thus will be affected in the same way by worker motions. Finally, using a blood oxygen sensor allowed the study to be conducted without exposing the human subjects to carbon monoxide. A user study was conducted to determine the distribution of motion artifacts that would be created during a typical work day. By comparing that distribution to a worst-case estimate of time to impairment, the probability that helmet will adequately monitor the worker can be established. The results of the study show that the helmet will provide a measurement capable of warning the user of on setting carbon monoxide poisoning with a probability greater than 99%. / Master of Science

In this thesis, an activity classification algorithm is developed to support a human ambulatory monitoring system. This algorithm, to be deployed on an e-textile garment, represents the enabling step in creating a wide range of garments that can use the same classifier without having to re-train for different sensor types. This flexible operation is made possible by basing the classifier on an abstract model of the human body that is the same across all sensor types and subject bodies. In order to support low power devices inherent for wearable systems, the algorithm utilizes regular expressions along with a tree search during classification. To validate the approach, a user study was conducted using video motion capture to record subjects performing a variety of activities. The subjects were randomly placed into two groups, one used to generate the activities known by the classifier and another to be used as observation to the classifier. These two sets were used to gain insight on the performance of the algorithm. The results of the study demonstrate that the algorithm can successfully classify observations, so as long as precautions are taken to prevent the activities known by the classifier to become too large. It is also shown that the tree search performed by the classification can be utilized to partially classify observations that would otherwise be rejected by the classifier. The user study additionally included subjects that performed activities purely used for observations to the classifier. With this set of recordings, it was demonstrated that the classifier does not over-fit and is capable of halting the classification of an observation. / Master of Science

Electrical components constantly being scaled down in size allows for small, inexpensive sensors to be placed on or around the human body for motion sensing applications. In addition, the merging of textiles with electrical components, known as electronic textiles (e-textiles), allows for these sensors to be placed directly on a wearable fabric. Simulation allows for extensive application testing and verification before prototype development. This thesis presents a simulation environment for motion sensing E-textiles. Specifically, this environment incorporates motion capture position data to simulate a rate sensing gyroscope and a dual-axis accelerometer. In addition, this simulation environment is applied to the field of gait analysis, which is the process of quantification and interpretation of a person's stride, to calculate a subject's step length. / Master of Science