Temporal Recurrent Networks for Online Action Detection

Most work on temporal action detection is formulated as an offline problem, in which the start and end times of actions are determined after the entire video is fully observed. However, important real-time applications including surveillance and driver assistance systems require identifying actions as soon as each video frame arrives, based only on current and historical observations. In this paper, we propose a novel framework, Temporal Recurrent Network (TRN), to model greater temporal context of a video frame by simultaneously performing online action detection and anticipation of the immediate future. At each moment in time, our approach makes use of both accumulated historical evidence and predicted future information to better recognize the action that is currently occurring, and integrates both of these into a unified end-to-end architecture. We evaluate our approach on two popular online action detection datasets, HDD and TVSeries, as well as another widely used dataset, THUMOS'14. The results show that TRN significantly outperforms the state-of-the-art

Emerging technologies in patient monitoring

The healthcare systems in the developed countries are changing rapidly. This is driven by socio-economic developments related to the aging population, the aggravating healthcare costs and the expected shortage of medical staff. These challenges might be – partially – addressed by more autonomous and intelligent patient monitoring with a trend to extend monitoring to lower acuity settings in hospitals or even at home. Currently technology options become available for patient monitoring and more integrated in our daily-lives, which have been originally developed for the consumer market such as miniaturized cameras, smart phones and tablet PC. This opens a wide range of opportunities for personal care, optimised privacy, comfort and family bonding

Camera on vessel:A camera-based system to measure change in water volume in a drinking glass

A major problem related to chronic health is patients’ “compliance” with new lifestyle changes, medical prescriptions, recommendations, or restrictions. Heart-failure and hemodialysis patients are usually placed on fluid restrictions due to their hemodynamic status. A holistic approach to managing fluid imbalance will incorporate the monitoring of salt-water intake, body-fluid retention, and fluid excretion in order to provide effective intervention at an early stage. Such an approach creates a need to develop a smart device that can monitor the drinking activities of the patient. This paper employs an empirical approach to infer the real water level in a conically shapped glass and the volume difference due to changes in water level. The method uses a low-resolution miniaturized camera to obtain images using an Arduino microcontroller. The images are processed in MATLAB. Conventional segmentation techniques (such as a Sobel filter to obtain a binary image) are applied to extract the level gradient, and an ellipsoidal fitting helps to estimate the size of the cup. The fitting (using least-squares criterion) between derived measurements in pixel and the real measurements shows a low covariance between the estimated measurement and the mean. The correlation between the estimated results to ground truth produced a variation of 3% from the mean

Non-invasive blood oxygen saturation monitoring for neonates using reflectance pulse oximeter

Blood oxygen saturation is one of the key parameters for health monitoring of premature infants at the neonatal intensive care unit (NICU). In this paper, we propose and demonstrate a design of a wearable wireless blood saturation monitoring system. Reflectance pulse oxymeter based on Near Infrared Spectroscopy (NIRS) techniques are applied for enhancing the flexibility of measurements at different locations on the body of the neonates and the compatibility to be integrated into a non-invasive monitoring platform, such as a neonatal smart jacket. Prototypes with the reflectance sensors embedded in soft fabrics are built. The thickness of device is minimized to optimize comfort. To evaluate the performance of the prototype, experiments on the premature babies were carried out at NICU of Máxima Medical Centre (MMC) in Veldhoven, the Netherlands. The results show that the heart rate and SpO2 measured by the proposed design are corresponding to the readings of the standard monitor

Klikker: a method and infrastructure for mining, analysis, and visualisation of user behaviour and usability issues for mobile application development

In the early stages of mobile application development, mockups can be used to receive feedback from potential end-users. This richness of feedback is limited by the lack of interactivity and requires a lot of time for a more significant study population. The Klikker methodology aims to unite the designer, developers, and end-users in the initial phases of development by utilising modern web technologies and readily available and interchangeable - design and analytic software. Klikker combines the collection of quantitative user behaviour and qualitative feedback from end-users on their own devices without additional effort from researchers. The method is intended to be deployed in the first few weeks of the development process

Enhancing lifestyle change in cardiac patients through the do change system ( Do cardiac health: Advanced new generation ecosystem ): Randomized controlled trial protocol

\u3cp\u3eBACKGROUND: Promoting a healthy lifestyle (eg, physical activity, healthy diet) is crucial for the primary and secondary prevention of cardiac disease in order to decrease disease burden and mortality.\u3c/p\u3e\u3cp\u3eOBJECTIVE: The current trial aims to evaluate the effectiveness of the Do Cardiac Health: Advanced New Generation Ecosystem (Do CHANGE) service, which is developed to assist cardiac patients in adopting a healthy lifestyle and improving their quality of life.\u3c/p\u3e\u3cp\u3eMETHODS: Cardiac patients (ie, people who have been diagnosed with heart failure, coronary artery disease, and/or hypertension) will be recruited at three pilot sites (Badalona Serveis Assistencials, Badalona, Spain [N=75]; Buddhist Tzu Chi Dalin General Hospital, Dalin, Taiwan [N=100] and Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands [N=75]). Patients will be assisted by the Do Something Different (DSD) program to change their unhealthy habits and/or lifestyle. DSD has been developed to increase behavioral flexibility and subsequently adopt new (healthier) habits. In addition, patients' progress will be monitored with a number of (newly developed) devices (eg, Fitbit, Beddit, COOKiT, FLUiT), which will be integrated in one application.\u3c/p\u3e\u3cp\u3eRESULTS: The Do CHANGE trial will provide us with new insights regarding the effectiveness of the proposed intervention in different cultural settings. In addition, it will give insight into what works for whom and why.\u3c/p\u3e\u3cp\u3eCONCLUSIONS: The Do CHANGE service integrates new technologies into a behavior change intervention in order to change the unhealthy lifestyles of cardiac patients. The program is expected to facilitate long-term, sustainable behavioral change.\u3c/p\u3e\u3cp\u3eTRIAL REGISTRATION: Clinicaltrials.gov NCT03178305; https://clinicaltrials.gov/ct2/show/NCT03178305 (Archived by WebCite at http://www.webcitation.org/6wfWHvuyU).\u3c/p\u3

Consume:A privacy-preserving authorisation and authentication service for connecting with health and wellbeing APIs

\u3cp\u3eThe growth of the Internet of Things (IoT) application within the health- and wellbeing domain enables individuals to monitor their health. Acquired data can be used privately, contribute to clinical databases, or for research. The amount of health and wellbeing tracking devices introduces complexity in data aggregation and scattered overviews. Few services exist to aggregate health data. Current services raise privacy concerns. Consume is a service for aggregating authentication and authorisation for Application Programming Interfaces (APIs). Consume aims at research and allows to add existing and custom APIs on-the-fly without restarting services.\u3c/p\u3

Design of an integrated sensor platform for vital sign monitoring of newborn infants at neonatal intensive care unit

Continuous health status monitoring and advances in medical treatments have resulted in a significant increase of survival rate in critically ill infants admitted into Neonatal Intensive Care Units (NICUs). The quality of life and long-term health prospects of the neonates depend increasingly on the reliability and comfort of the monitoring systems. In this paper, we present the design work of a smart jacket for vital sign monitoring of neonates at a NICU. The design represents a unique integration of sensor technology, user focus and design aspects. Textile sensors, a reflectance pulse oximeter and a wearable temperature sensor were proposed to be embedded into the smart jacket. Location of the sensor, materials and appearance were designed to optimize the functionality, patient comfort and the possibilities for aesthetic features. Prototypes were built for demonstrating the design concept and experimental results were obtained from tests on premature babies at the NICU of Máxima Medical Centre (MMC) in Veldhoven, the Netherlands