Watermarking of audio signals using independent component analysis

A novel approach to watermarking of audio signals using Independent Component Analysis (ICA) is proposed. It exploits the statistical independence of components obtained by practical ICA algorithms to provide a robust watermarking scheme with high information rate and low distortion. Numerical simulations have been performed on audio signals, showing good robustness of the watermark against common attacks with unnoticeable distortion, even for high information rates. An important aspect of the method is its domain independence: it can be used to hide information in other types of data, with minor technical adaptations.

Human-computer interaction and innovation in handheld, mobile and wearable technologies

Handheld and mobile technologies have witnessed significant advances in functionality, leading to their widespread use as both business and social networking tools. Human-Computer Interaction and Innovation in Handheld, Mobile and Wearable Technologies reviews concepts relating to the design, development, evaluation, and application of mobile technologies. Studies on mobile user interfaces, mobile learning, and mobile commerce contribute to the growing body of knowledge on this expanding discipline.

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A paradigm shift:alternative interaction techniques for use with mobile & wearable devices

Desktop user interface design originates from the fact that users are stationary and can devote all of their visual resource to the application with which they are interacting. In contrast, users of mobile and wearable devices are typically in motion whilst using their device which means that they cannot devote all or any of their visual resource to interaction with the mobile application -- it must remain with the primary task, often for safety reasons. Additionally, such devices have limited screen real estate and traditional input and output capabilities are generally restricted. Consequently, if we are to develop effective applications for use on mobile or wearable technology, we must embrace a paradigm shift with respect to the interaction techniques we employ for communication with such devices.This paper discusses why it is necessary to embrace a paradigm shift in terms of interaction techniques for mobile technology and presents two novel multimodal interaction techniques which are effective alternatives to traditional, visual-centric interface designs on mobile devices as empirical examples of the potential to achieve this shift.

Multimodal 'Eyes-Free' interaction techniques for mobile devices

Mobile and wearable computers present input/output prob-lems due to limited screen space and interaction techniques. When mobile, users typically focus their visual attention on navigating their environment - making visually demanding interface designs hard to operate. This paper presents two multimodal interaction techniques designed to overcome these problems and allow truly mobile, 'eyes-free' device use. The first is a 3D audio radial pie menu that uses head gestures for selecting items. An evaluation of a range of different audio designs showed that egocentric sounds re-duced task completion time, perceived annoyance, and al-lowed users to walk closer to their preferred walking speed. The second is a sonically enhanced 2D gesture recognition system for use on a belt-mounted PDA. An evaluation of the system with and without audio feedback showed users' ges-tures were more accurate when dynamically guided by au-dio-feedback. These novel interaction techniques demon-strate effective alternatives to visual-centric interface de-signs on mobile devices.

Guidelines for audio-enhancement of graphical user Interface widgets

Audio feedback remains little used in most graphical user interfaces despite its potential to greatly enhance interaction. Not only does sonic enhancement of interfaces permit more natural human-computer communication but it also allows users to employ an appropriate sense to solve a problem rather than having to rely solely on vision. Research shows that designers do not typically know how to use sound effectively; subsequently, their ad hoc use of sound often leads to audio feedback being considered an annoying distraction. Unlike the design of purely graphical user interfaces for which guidelines are common, the audio-enhancement of graphical user interfaces has (until now) been plagued by a lack of suitable guidance. This paper presents a series of empirically substantiated guidelines for the design and use of audio-enhanced graphical user interface widgets.

A wearable device for recording of biopotentials and body movements

Long term recording of biomedical signals such as ECG, EMG, respiration and other information (e.g. body motion) can improve diagnosis and potentially monitor the evolution of many widespread diseases. However, long term monitoring requires specific solutions, portable and wearable equipment that should be particularly comfortable for patients. The key-issues of portable biomedical instrumentation are: power consumption, long-term sensor stability, comfortable wearing and wireless connectivity. In this scenario, it would be valuable to realize prototypes using available technologies to assess long-term personal monitoring and foster new ways to provide healthcare services. The aim of this work is to discuss the advantages and the drawbacks in long term monitoring of biopotentials and body movements using textile electrodes embedded in clothes. The textile electrodes were embedded into garments; tiny shirt and short were used to acquire electrocardiographic and electromyographic signals. The garment was equipped with low power electronics for signal acquisition and data wireless transmission via Bluetooth. A small, battery powered, biopotential amplifier and three-axes acceleration body monitor was realized. Patient monitor incorporates a microcontroller, analog-to-digital signal conversion at programmable sampling frequencies. The system was able to acquire and to transmit real-time signals, within 10 m range, to any Bluetooth device (including PDA or cellular phone). The electronics were embedded in the shirt resulting comfortable to wear for patients. Small size MEMS 3-axes accelerometers were also integrated. © 2011 IEEE.

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice. © 2016 International Parkinson and Movement Disorder Society.

Re-visualising international relations:audio-visual projects and direct encounters with the political in security studies

In this paper we discuss how an innovative audio-visual project was adopted to foster active, rather than declarative learning, in critical International Relations (IR). First, we explore the aesthetic turn in IR, to contrast this with forms of representation that have dominated IR scholarship. Second, we describe how students were asked to record short audio or video projects to explore their own insights through aesthetic and non-written formats. Third, we explain how these projects are understood to be deeply embedded in social science methodologies. We cite our inspiration from applying a personal sociological imagination, as a way to counterbalance a ‘marketised’ slant in higher education, in a global economy where students are often encouraged to consume, rather than produce knowledge. Finally, we draw conclusions in terms of deeper forms of student engagement leading to new ways of thinking and presenting new skills and new connections between theory and practice.

Wearable sensors in Huntington disease:a pilot study

Background: The Unified Huntington’s Disease Rating Scale (UHDRS) is the principal means of assessing motor impairment in Huntington disease but is subjective and generally limited to in-clinic assessments. Objective: To evaluate the feasibility and ability of wearable sensors to measure motor impairment in individuals with Huntington disease in the clinic and at home. Methods: Participants with Huntington disease and controls were asked to wear five accelerometer-based sensors attached to the chest and each limb for standardized, in-clinic assessments and for one day at home. A secondchest sensor was worn for six additional days at home. Gait measures were compared between controls, participants with Huntington disease, and participants with Huntington disease grouped by UHDRS total motor score using Cohen’s d values. Results: Fifteen individuals with Huntington disease and five controls completed the study. Sensor data were successfully captured from 18 of the 20 participants at home. In the clinic, the standard deviation of step time (timebetween consecutive steps) was increased in Huntington disease (p<0.0001; Cohen’s d=2.61) compared to controls. At home with additional observations, significant differences were observed in seven additional gait measures. The gait of individuals with higher total motor scores (50 or more) differed significantly from those with lower total motor scores (below 50) on multiple measures at home. Conclusions: In this pilot study, the use of wearable sensors in clinic and at home was feasible and demonstrated gait differences between controls, participants with Huntington disease, and participants with Huntington diseasegrouped by motor impairment.