Using an Audience Response System Smartphone App to Improve Resident Education in the Pediatric Intensive Care Unit.

In the Pediatric Intensive Care Unit (PICU), most teaching occurs during bedside rounds, but technology now provides new opportunities to enhance education. Specifically, smartphone apps allow rapid communication between instructor and student. We hypothesized that using an audience response system (ARS) app can identify resident knowledge gaps, guide teaching, and enhance education in the PICU. Third-year pediatric residents rotating through the PICU participated in ARS-based education or received traditional teaching. Before rounds, experimental subjects completed an ARS quiz using the Socrative app. Concomitantly, the fellow leading rounds predicted quiz performance. Then, discussion points based on the incorrect answers were used to guide instruction. Scores on the pre-rotation test were similar between groups. On the post-rotation examination, ARS participants did not increase their scores more than controls. The fellow's prediction of performance was poor. Residents felt that the method enhanced their education whereas fellows reported that it improved their teaching efficiency. Although there was no measurable increase in knowledge using the ARS app, it may still be a useful tool to rapidly assess learners and help instructors provide learner-centered education

Using smartphones as a proxy for forensic evidence contained in cloud storage services

Cloud storage services such as Dropbox, Box and SugarSync have been embraced by both individuals and organizations. This creates an environment that is potentially conducive to security breaches and malicious activities. The investigation of these cloud environments presents new challenges for the digital forensics community. It is anticipated that smartphone devices will retain data from these storage services. Hence, this research presents a preliminary investigation into the residual artifacts created on an iOS and Android device that has accessed a cloud storage service. The contribution of this paper is twofold. First, it provides an initial assessment on the extent to which cloud storage data is stored on these client-side devices. This view acts as a proxy for data stored in the cloud. Secondly, it provides documentation on the artifacts that could be useful in a digital forensics investigation of cloud services

Recovering Residual Forensic Data from Smartphone Interactions with Cloud Storage Providers

There is a growing demand for cloud storage services such as Dropbox, Box, Syncplicity and SugarSync. These public cloud storage services can store gigabytes of corporate and personal data in remote data centres around the world, which can then be synchronized to multiple devices. This creates an environment which is potentially conducive to security incidents, data breaches and other malicious activities. The forensic investigation of public cloud environments presents a number of new challenges for the digital forensics community. However, it is anticipated that end-devices such as smartphones, will retain data from these cloud storage services. This research investigates how forensic tools that are currently available to practitioners can be used to provide a practical solution for the problems related to investigating cloud storage environments. The research contribution is threefold. First, the findings from this research support the idea that end-devices which have been used to access cloud storage services can be used to provide a partial view of the evidence stored in the cloud service. Second, the research provides a comparison of the number of files which can be recovered from different versions of cloud storage applications. In doing so, it also supports the idea that amalgamating the files recovered from more than one device can result in the recovery of a more complete dataset. Third, the chapter contributes to the documentation and evidentiary discussion of the artefacts created from specific cloud storage applications and different versions of these applications on iOS and Android smartphones

Word Adjacency Graph Modeling: Separating Signal From Noise in Big Data

There is a need to develop methods to analyze Big Data to inform patient-centered interventions for better health outcomes. The purpose of this study was to develop and test a method to explore Big Data to describe salient health concerns of people with epilepsy. Specifically, we used Word Adjacency Graph modeling to explore a data set containing 1.9 billion anonymous text queries submitted to the ChaCha question and answer service to (a) detect clusters of epilepsy-related topics, and (b) visualize the range of epilepsy-related topics and their mutual proximity to uncover the breadth and depth of particular topics and groups of users. Applied to a large, complex data set, this method successfully identified clusters of epilepsy-related topics while allowing for separation of potentially non-relevant topics. The method can be used to identify patient-driven research questions from large social media data sets and results can inform the development of patient-centered interventions

An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics

Near-sensor data analytics is a promising direction for IoT endpoints, as it minimizes energy spent on communication and reduces network load - but it also poses security concerns, as valuable data is stored or sent over the network at various stages of the analytics pipeline. Using encryption to protect sensitive data at the boundary of the on-chip analytics engine is a way to address data security issues. To cope with the combined workload of analytics and encryption in a tight power envelope, we propose Fulmine, a System-on-Chip based on a tightly-coupled multi-core cluster augmented with specialized blocks for compute-intensive data processing and encryption functions, supporting software programmability for regular computing tasks. The Fulmine SoC, fabricated in 65nm technology, consumes less than 20mW on average at 0.8V achieving an efficiency of up to 70pJ/B in encryption, 50pJ/px in convolution, or up to 25MIPS/mW in software. As a strong argument for real-life flexible application of our platform, we show experimental results for three secure analytics use cases: secure autonomous aerial surveillance with a state-of-the-art deep CNN consuming 3.16pJ per equivalent RISC op; local CNN-based face detection with secured remote recognition in 5.74pJ/op; and seizure detection with encrypted data collection from EEG within 12.7pJ/op.Comment: 15 pages, 12 figures, accepted for publication to the IEEE Transactions on Circuits and Systems - I: Regular Paper

Evaluation of E-Health Applications for Paediatric Patients with Refractory Epilepsy and Maintained on Ketogenic Diet

E-health technologies improve healthcare quality and disease management. The aim of this study was to develop a ketogenic diet management app as well as a website about this dietary treatment and to evaluate the benefits of giving caregivers access to various web materials designed for paediatric patients with refractory epilepsy. Forty families participated in the questionnaire survey, from January 2016 to March 2016. All caregivers were exposed to paper-based materials about the ketogenic diet, whereas only 22 received the app, called KetApp, and videos produced by dieticians. Caregivers with free access to web materials were more satisfied than the others with the informative material provided by the centre (p 64 0.001, Mann\u2013Whitney test). Indeed, they showed a better attitude towards treatment, and they became more aware of dietary management in comparison to the control group (p 64 0.001). Moreover, caregivers provided with web materials were stimulated to pursue the treatment (p = 0.002) and to introduce it to their children and other people (p = 0.001). Additionally, caregivers supplied with web materials were more willing to help other families in choosing the ketogenic diet (p = 0.004). Overall, these findings indicate that web materials are beneficial for caregivers of paediatric patients with refractory epilepsy in our centres. Thus, the use of e-health applications could be a promising tool in the daily aspects of ketogenic diet management, and it is especially of value in the attempt to start or maintain the diet during the ongoing COVID-19 pandemic crisis

A User-centered Smartphone Application for Wireless EEG and its Role in Epilepsy

Electroencephalography is well-known for its importance in the diagnosis and treatment of mental and neurological disorders and abnormalities, being especially noted in critically ill patients who suffer a variety of cerebral injuries and altered states of consciousness. However, there is an important lack of adapted equipment and applications designed to suit the clinical and research needs. Hence, patients, physicians and researchers suffer, in most cases, from a restricted mobility due to non-portable devices and wires which keep them attached to the bed, leading to an uncomfortable patient experience or difficulties during the recording. In addition, nowadays, both physicians and researchers need to access the recordings and patient information from different places such as different units or hospitals. To solve this problem, this paper presents the design and evaluation of the high-fidelity prototype of a wireless EEG smartphone application based on a user-centred design, including expert panel guidance, paper and high-fidelity prototyping and usability testing, which confirm the accuracy of the defined context of use and the validity of the prototyped application to suit the clinical and research needs. In fact, since the EEG is the most efficient and specific way to define the epileptogenic cortex, we will focus on the possible use of the presented App in epilepsy diagnosis, which is one of the main targets in the field