A scheme is developed for classifying the types of motion perceived by a humanlike robot. It is assumed that the robot receives visual images of the scene using a perspective system model. Equations, theorems, concepts, clues, etc., relating the objects, their positions, and their motion to their images on the focal plane are presented. >

http://ieeexplore.ieee.org/iel2/815/3148/00100651.pdf

Robot vision

Advanced mobile communications and portable computation are now combined in handheld devices called “smartphones”, which are also capable of running third-party software. The number of smartphone users is growing rapidly, including among healthcare professionals. The purpose of this study was to classify smartphone-based healthcare technologies as discussed in academic literature according to their functionalities, and summarize articles in each category. In April 2011, MEDLINE was searched to identify articles that discussed the design, development, evaluation, or use of smartphone-based software for healthcare professionals, medical or nursing students, or patients. A total of 55 articles discussing 83 applications were selected for this study from 2,894 articles initially obtained from the MEDLINE searches. A total of 83 applications were documented: 57 applications for healthcare professionals focusing on disease diagnosis (21), drug reference (6), medical calculators (8), literature search (6), clinical communication (3), Hospital Information System (HIS) client applications (4), medical training (2) and general healthcare applications (7); 11 applications for medical or nursing students focusing on medical education; and 15 applications for patients focusing on disease management with chronic illness (6), ENT-related (4), fall-related (3), and two other conditions (2). The disease diagnosis, drug reference, and medical calculator applications were reported as most useful by healthcare professionals and medical or nursing students. Many medical applications for smartphones have been developed and widely used by health professionals and patients. The use of smartphones is getting more attention in healthcare day by day. Medical applications make smartphones useful tools in the practice of evidence-based medicine at the point of care, in addition to their use in mobile clinical communication. Also, smartphones can play a very important role in patient education, disease self-management, and remote monitoring of patients.

/pdf/a-systematic-review-of-healthcare-applications-for-2xnx964c6m.pdf

A Systematic Review of Healthcare Applications for Smartphones

MRI-based medical image analysis for brain tumor studies is gaining attention in recent times due to an increased need for efficient and objective evaluation of large amounts of data. While the pioneering approaches applying automated methods for the analysis of brain tumor images date back almost two decades, the current methods are becoming more mature and coming closer to routine clinical application. This review aims to provide a comprehensive overview by giving a brief introduction to brain tumors and imaging of brain tumors first. Then, we review the state of the art in segmentation, registration and modeling related to tumor-bearing brain images with a focus on gliomas. The objective in the segmentation is outlining the tumor including its sub-compartments and surrounding tissues, while the main challenge in registration and modeling is the handling of morphological changes caused by the tumor. The qualities of different approaches are discussed with a focus on methods that can be applied on standard clinical imaging protocols. Finally, a critical assessment of the current state is performed and future developments and trends are addressed, giving special attention to recent developments in radiological tumor assessment guidelines.

/pdf/a-survey-of-mri-based-medical-image-analysis-for-brain-tumor-4mtl4fktmo.pdf

A survey of MRI-based medical image analysis for brain tumor studies

M-Health can be defined as “mobile computing, medical sensor, and communications technologies for health-care.” This emerging concept represents the evolution of e-health systems from traditional desktop “telemedicine” platforms to wireless and mobile configurations. Current and emerging developments in wireless communications integrated with developments in pervasive and wearable technologies will have a radical impact on future health-care delivery systems. This editorial paper presents a snapshot of recent developments in these areas and addresses some of the challenges and future implementation issues from the m-Health perspective. The contributions presented in this special section represent some of these recent developments and illustrate the multidisciplinary nature of this important and emerging concept.

/pdf/guest-editorial-introduction-to-the-special-section-on-m-4wo531cl4n.pdf

Guest Editorial Introduction to the Special Section on M-Health: Beyond Seamless Mobility and Global Wireless Health-Care Connectivity

Ubiquitous blood pressure (BP) monitoring is needed to improve hypertension detection and control and is becoming feasible due to recent technological advances such as in wearable sensing. Pulse transit time (PTT) represents a well-known potential approach for ubiquitous BP monitoring. The goal of this review is to facilitate the achievement of reliable ubiquitous BP monitoring via PTT. We explain the conventional BP measurement methods and their limitations; present models to summarize the theory of the PTT-BP relationship; outline the approach while pinpointing the key challenges; overview the previous work toward putting the theory to practice; make suggestions for best practice and future research; and discuss realistic expectations for the approach.

/pdf/toward-ubiquitous-blood-pressure-monitoring-via-pulse-3274861uea.pdf

Toward Ubiquitous Blood Pressure Monitoring via Pulse Transit Time: Theory and Practice.

Heart Beat Rate calculation has traditionally been conducted using specialized hardware most commonly in the form of pulse oximeters or Electrocardiogram devices. Even though these methods offer high reliability, they require the users to have special sensor to measure their heart rate. In this paper we propose a system capable of estimating the heart beat rate using just a camera from a commercially available mobile phone. The advantage of this method is that the user does not need specialized hardware and s/he can take a measurement in virtually any place under almost any circumstances. Moreover the measurement provided can be used as a tool for health coaching applications or effective telecare services aimed in enhancing the user's well being.

A novel method to detect Heart Beat Rate using a mobile phone

Recent advances in the hardware of handheld devices, opened up the way for newer applications in the healthcare sector, and more specifically, in the teleconsultation field Out of these devices, this paper focuses on the services that personal digital assistants and smartphones can provide to improve the speed, quality and ease of delivering a medical opinion from a distance and laying the ground for an all-wireless hospital In that manner, PDAs were used to wirelessly support the viewing of digital imaging and communication in medicine (DICOM) images and to allow for mobile videoconferencing while within the hospital Smartphones were also used to carry still images, multiframes and live video outside the hospital Both of these applications aimed at increasing the mobility of the consultant while improving the healthcare service

/pdf/using-handheld-devices-for-real-time-wireless-2ft7t31fd1.pdf

Using handheld devices for real-time wireless teleconsultation

We developed a mobile teleconsultation system based on third-generation mobile phone links. The system comprised a laptop computer and a digital camcorder. It was installed inside an ambulance to allow video-conferencing between the moving vehicle and a doctor at a base station. In addition to video and voice, high-quality still images could also be transmitted. A series of 17 trial runs with real ambulance patients was conducted in the city of Athens. In general, the videoconferencing sessions produced relatively clear video. The bandwidth was high enough for a satisfactory video of 10-15 frames/s. During a total testing period of 23 h and in an area of about 180 km2, there were nine instances of signal loss, amounting to a total of 17 min. The general opinion formed by the doctors was that the system produced good results. All initial diagnoses made using the system agreed with the final diagnoses of the patients. The study showed that the mobile system could reduce the time before an ambulance patient is seen by a doctor.

/pdf/use-of-3g-mobile-phone-links-for-teleconsultation-between-a-3n10qsjg3k.pdf

Use of 3G mobile phone links for teleconsultation between a moving ambulance and a hospital base station

This is a post-peer-review, pre-copyedit version of an article published in Journal of Medical Marketing. The definitive publisher-authenticated version "Konstantinos A. Banitsas, R.S.H. Istepanian, Sapal Tachakra. Applications of medical Wireless LAN systems (MedLAN). Journal of Medical Marketing, Volume 2, Number 2, 1 January 2002 , pp. 136-142(7)" is available online at: http://www.ingentaconnect.com/content/pal/jomm/2002/00000002/00000002/art00008.

/pdf/applications-of-medical-wireless-lan-systems-medlan-2jjv6uklmx.pdf

Applications of medical wireless LAN systems (MedLAN)

Freezing of Gait (FOG) is a disabling symptom and movement disorder, typically associated with the latter stages of Parkinson's disease. In this paper, we propose a novel approach for real-time FOG, tremor monitoring and fall detection, consisting of a 3D camera sensor based on the Microsoft Kinect architecture. The system is capable of recognizing freezing episodes (FOG) in a standstill state, tremors and fall incidents, commonly seen in Parkinson's disease patients. In case of an incident, it automatically alerts relatives and healthcare providers. The system was tested on seven simulated subjects in 12 events indicating that the design was able to detect 99% of the falling incidents, 91% of tremor and 92% of the freezing of gait episodes with an average latency of 300 milliseconds. The performance of the system can be further improved with the deployment of the recently released version of Kinect, capable of providing even higher levels of accuracy.

/pdf/recognition-of-postures-and-freezing-of-gait-in-parkinson-s-1dnmnthtvo.pdf

Konstantinos Banitsas

Papers

A novel method to detect Heart Beat Rate using a mobile phone

Using handheld devices for real-time wireless teleconsultation

Use of 3G mobile phone links for teleconsultation between a moving ambulance and a hospital base station

Applications of medical wireless LAN systems (MedLAN)

Recognition of postures and Freezing of Gait in Parkinson's disease patients using Microsoft Kinect sensor