Exploring glass as a novel method for hands-free data entry in flexible cystoscopy

We present a way to annotate cystoscopy finding on Google Glass in a reproducible and hands free manner for use by surgeons during operations in the sterile environment inspired by the current practice of hand-drawn sketches. We developed three data entry variants based on speech and head movements. We assessed the feasibility, benefits and drawbacks of the system with 8 surgeons and Foundation Doctors having up to 30 years' cystoscopy experience at a UK hospital in laboratory trials. We report data entry speed and error rate of input modalities and contrast it with the participants' feedback on their perception of usability, acceptance, and suitability for deployment. The results are supportive of new data entry technologies and point out directions for future improvement of eyewear computers. The findings can be generalised to other endoscopic procedures (e.g. OGD/laryngoscopy) and could be included within hospital IT in the future

Enriching mobile interaction with garment-based wearable computing devices

Wearable computing is on the brink of moving from research to mainstream. The first simple products, such as fitness wristbands and smart watches, hit the mass market and achieved considerable market penetration. However, the number and versatility of research prototypes in the field of wearable computing is far beyond the available devices on the market. Particularly, smart garments as a specific type of wearable computer, have high potential to change the way we interact with computing systems. Due to the proximity to the user`s body, smart garments allow to unobtrusively sense implicit and explicit user input. Smart garments are capable of sensing physiological information, detecting touch input, and recognizing the movement of the user. In this thesis, we explore how smart garments can enrich mobile interaction. Employing a user-centered design process, we demonstrate how different input and output modalities can enrich interaction capabilities of mobile devices such as mobile phones or smart watches. To understand the context of use, we chart the design space for mobile interaction through wearable devices. We focus on the device placement on the body as well as interaction modality. We use a probe-based research approach to systematically investigate the possible inputs and outputs for garment based wearable computing devices. We develop six different research probes showing how mobile interaction benefits from wearable computing devices and what requirements these devices pose for mobile operating systems. On the input side, we look at explicit input using touch and mid-air gestures as well as implicit input using physiological signals. Although touch input is well known from mobile devices, the limited screen real estate as well as the occlusion of the display by the input finger are challenges that can be overcome with touch-enabled garments. Additionally, mid-air gestures provide a more sophisticated and abstract form of input. We present a gesture elicitation study to address the special requirements of mobile interaction and present the resulting gesture set. As garments are worn, they allow different physiological signals to be sensed. We explore how we can leverage these physiological signals for implicit input. We conduct a study assessing physiological information by focusing on the workload of drivers in an automotive setting. We show that we can infer the driver´s workload using these physiological signals. Beside the input capabilities of garments, we explore how garments can be used as output. We present research probes covering the most important output modalities, namely visual, auditory, and haptic. We explore how low resolution displays can serve as a context display and how and where content should be placed on such a display. For auditory output, we investigate a novel authentication mechanism utilizing the closeness of wearable devices to the body. We show that by probing audio cues through the head of the user and re-recording them, user authentication is feasible. Last, we investigate EMS as a haptic feedback method. We show that by actuating the user`s body, an embodied form of haptic feedback can be achieved. From the aforementioned research probes, we distilled a set of design recommendations. These recommendations are grouped into interaction-based and technology-based recommendations and serve as a basis for designing novel ways of mobile interaction. We implement a system based on these recommendations. The system supports developers in integrating wearable sensors and actuators by providing an easy to use API for accessing these devices. In conclusion, this thesis broadens the understanding of how garment-based wearable computing devices can enrich mobile interaction. It outlines challenges and opportunities on an interaction and technological level. The unique characteristics of smart garments make them a promising technology for making the next step in mobile interaction

Fun weight

Treball desenvolupat dins el marc del programa 'European Project Semester' i l'"International Design Project Semester".The main objective of the Fun Weight project was to decrease the level of anxiety from children during preoperative treatment, while the gathering of measurements essential for further hospitalization takes place. This assignment has been conducted by an international and multidisciplinary team whose members were from fields of: Product Design, Electronics and Information Communication Technologies, Mechanical Engineering and Information Technology. The project was interesting and constructive due to tight cooperation with the Hospital de Sant Joan de Deu in Barcelona which was the main stakeholder of this project. Methodology of the project consisted of in advance strictly defined steps, which were: researching, designing of the interactive game, designing/development of the application, prototyping of the application, prototyping of the interactive game and testing. However the development of the interactive game and the application have been performed simultaneously. The outcome of this project has reached its end at the 17th of June and concluded following three elements: electronical prototype of the interactive game, three dimensional model of the game and the mobile application for retrieving measurements and communicating with the interactive game. The stage of testing was divided into three independent sections: testing of the application usability, testing of the application functionality and evaluation of actual anxiety decreasing. As a result of application usability test, an average rate of ease of the interface has been obtained at the level of 2 what states for easy to use. Functionality tests have been performed with application of the Angel Sensor in function of the measuring device. In spite of problems encountered during the use of that sensor, basic functionalities of the application have been confirmed. Due to the shortage of the time, evaluation of decrease of anxiety level has not yet been conducted

Detecting head movement using gyroscope data collected via in-ear wearables

Abstract. Head movement is considered as an effective, natural, and simple method to determine the pointing towards an object. Head movement detection technology has significant potentiality in diverse field of applications and studies in this field verify such claim. The application includes fields like users interaction with computers, controlling many devices externally, power wheelchair operation, detecting drivers’ drowsiness while they drive, video surveillance system, and many more. Due to the diversity in application, the method of detecting head movement is also wide-ranging. A number of approaches such as acoustic-based, video-based, computer-vision based, inertial sensor data based head movement detection methods have been introduced by researchers over the years. In order to generate inertial sensor data, various types of wearables are available for example wrist band, smart watch, head-mounted device, and so on. For this thesis, eSense — a representative earable device — that has built-in inertial sensor to generate gyroscope data is employed. This eSense device is a True Wireless Stereo (TWS) earbud. It is augmented with some key equipment such as a 6-axis inertial motion unit, a microphone, and dual mode Bluetooth (Bluetooth Classic and Bluetooth Low Energy). Features are extracted from gyroscope data collected via eSense device. Subsequently, four machine learning models — Random Forest (RF), Support Vector Machine (SVM), Naïve Bayes, and Perceptron — are applied aiming to detect head movement. The performance of these models is evaluated by four different evaluation metrics such as Accuracy, Precision, Recall, and F1 score. Result shows that machine learning models that have been applied in this thesis are able to detect head movement. Comparing the performance of all these machine learning models, Random Forest performs better than others, it is able to detect head movement with approximately 77% accuracy. The accuracy rate of other three models such as Support Vector Machine, Naïve Bayes, and Perceptron is close to each other, where these models detect head movement with about 42%, 40%, and 39% accuracy, respectively. Besides, the result of other evaluation metrics like Precision, Recall, and F1 score verifies that using these machine learning models, different head direction such as left, right, or straight can be detected

The Next Familiar

Using a speculative design foresight approach, this study explores the rapidly developing area of wearable, implantable and ingestible technologies, and how they might influence us over the next several decades. The authors have combined traditional research methods such as literature review and expert interviews; foresight methods, such as environmental scanning, trends analysis and scenario creation; and narrative, imagery and conjecture to produce an evocative account of future possibilities in the realm of the tools we keep and use close to and inside our bodies

2016 Oklahoma Research Day Full Program

This document contains all abstracts from the 2016 Oklahoma Research Day held at Northeastern State University