Improving Patient Care With Telemedicine Technology

With the spread of telecommunications infrastructure, telemedicine has attracted attention from both healthcare and IT industries. Telemedicine has shown a potential to improve health maintenance, enhancement, as well as healthcare cost reduction. Many governments are boosting telemedicine applications through regulations. The purpose of this chapter is to review the major telemedicine technologies—telemedicine, wearable devices, and emerging innovative health equipment—and current issues of the impact on the patient care in the healthcare industry, the business opportunities, and threats from telemedicine.

Doctor-Patient Social Networking to Improve Specialist Care Coordination

Effective communication and coordination among medical doctors, specialists, and other caregivers could mean the difference between life and death for patients. This chapter presents a new digital health technology paradigm based on social networking that improves care coordination and communication among medical specialists. This technology integrates data across diagnostic modalities to simplify the process of accessing information, and reporting medical interpretations and treatment recommendations. This model can help care providers improve patient outcomes by facilitating initial risk stratification and remote consults with experts, thereby reducing admissions and readmissions, and making patient care more effective. Additionally, this technology can address the lack of specialists in underserved areas, and ease accessibility for aging populations.

Regulatory Issues in Telehealth

Telehealth and digital health more broadly have become two of the fastest growing IT sectors in the world. They have the potential to transform lives everywhere, often before regulation has had the chance to catch up to everyday reality in healthcare. This chapter is grounded in clinical practice occurring at the time of writing and discusses at a high level regulatory issues in telehealth. This chapter argues that complexities regarding regulation over clinical applicability, patient identification, bandwidth, and funding mechanisms, as well as data storage, jurisdiction, and usage should not prevent uptake of telehealth and digital health given the clinical benefits of telehealth in countries such as Australia and internationally.

Adaptive Prediction Methods for Medical Image/Video compression for Telemedicine Application

Due to rapid development of multimedia communication and advancement of image acquisition process, there is a crucial requirement of high storage and compression techniques to mitigate high data rate with limited bandwidth scenario for telemedicine application. Lossless compression is one of the challenging tasks in applications like medical, space, and aerial imaging field. Apart from achieving high compression ratio, in these mentioned applications there is a need to maintain the original imaging quality along with fast and adequate processing. Predictive coding was introduced to remove spatial redundancy. The accuracy of predictive coding is based on the choice of effective and adaptive predictor which is responsible for removing spatial redundancy. Medical images like computed tomography (CT) and magnetic resonance imaging (MRI) consume huge storage and utilize maximum available bandwidth. To overcome these inherent challenges, the authors have reviewed various adaptive predictors and it has been compared with existing JPEG and JPEG LS-based linear prediction technique for medical images.

Performance Analysis of Compression Techniques for Chronic Wound Image Transmission Under Smartphone-Enabled Tele-Wound Network

The healing status of chronic wounds is important for monitoring the condition of the wounds. This article designs and discusses the implementation of smartphone-enabled compression technique under a tele-wound network (TWN) system. Nowadays, there is a huge demand for memory and bandwidth savings for clinical data processing. Wound images are captured using a smartphone through a metadata application page. Then, they are compressed and sent to the telemedical hub with a set partitioning in hierarchical tree (SPIHT) compression algorithm. The transmitted image can then be reduced, followed by an improvement in the segmentation accuracy and sensitivity. Better wound healing treatment depends on segmentation and classification accuracy. The proposed framework is evaluated in terms of rates (bits per pixel), compression ratio, peak signal to noise ratio, transmission time, mean square error and diagnostic quality under telemedicine framework. A SPIHT compression technique assisted YDbDr-Fuzzy c-means clustering considerably reduces the execution time (105s), is simple to implement, saves memory (18 KB), improves segmentation accuracy (98.39%), and yields better results than the same without using SPIHT. The results favor the possibility of developing a practical smartphone-enabled telemedicine system and show the potential for being implemented in the field of clinical evaluation and the management of chronic wounds in the future.

Mobile Health and Telemedicine

In 2016, the U.S. Government health expenditures reached $3.35 trillion and the cost per person stood at $10,345. Health is seen as impacting both one's quality of life and finances. The Affordable Care Act (ACA) (2008 - 2016) brought the issue of cost to the forefront for all people especially those in the health disparate communities. Advances in health informatics coupled with new approaches to healthcare delivery may hold promise for this large industry in the USA that critically needs to be cost effective in order to sustain itself. This paper reports a study that investigated importance of health, mobile health (m-Health) and telemedicine awareness along with its adoption in a health disparate community that has one of the Historical Black Colleges & Universities (HBCUs) in the country. The findings were that, all participants owned a mobile (cell) phone with smart features. Although a large number them indicated that their health was very important to them, there was lack of awareness and adoption of m-Health and telemedicine.

Secure and Robust Telemedicine using ECC on Radix-8 with Formal Verification

The scalar multiplication techniques used in Elliptic curve cryptography (ECC) are having the scope for gaining the computation efficiency. This is possible through the reduction of precomputed operations. Finding the more efficient technique compares to the most recent or efficient one is a research gap for all schemes. The manuscript presents an application oriented work for Telemedicine using ECC. It is based on robust application on reduced computational complexity. The methodology we apply for the same is Scalar Multiplication without precomputation on Radix-8. Introduced software and the hardware performance are reporting a big advantage over all the related proposed techniques. The reason to cover this problem is to provide a path on a fascinating area of ECC on a smaller key size be applicable for all applications on a same level of security strengths. The smaller length key gives the higher speed and shorter clock cycle to initiate the operation.

Digital Health Innovation Enhancing Patient Experience in Medical Travel

Digital health technological innovations are disrupting every sector of the economy, including medical travel/tourism. Global patients as medical tourists are using patient-centric digital health technologies, enhancing patient/medical tourists experience and making it more transparent and engaging with healthcare providers and medical tourists. Digital communication tools such as e-mail, online appointments, smartphones, instant messaging applications, social media tools, user-generated content by online patient communities, tele-medicine, tele-radiology, my-Health records, Skype consultation, WhatsApp, health video, electronic health records, health data analytics tools, and artificial intelligence-enabled health technologies enhance the medical travel decision-making process, reduce cost, improve patient care and transparency of communication, and engage the relationship between the patient and the healthcare provider with positive outcomes, medical tourist experience, and empowerment.

A FRT - SVD Based Blind Medical Watermarking Technique for Telemedicine Applications

In this article, a blind and robust medical image watermarking technique based on Finite Ridgelet Transform (FRT) and Singular Value Decomposition (SVD) is proposed. A host medical image is first transformed into 16 × 16 non-overlapping blocks and then ridgelet transform is applied on the individual blocks to obtain sets of ridgelet coefficients. SVD is then applied on these sets, to obtain the corresponding U, S and V matrix. The watermark information is embedded into the host medical image by modification of the value of the significant elements of U matrix. This proposed technique is tested on various types of medical images such as X-ray and CT scan. The simulation results revealed that this technique provides better imperceptibility, with an average PSNR being 42.95 dB for all test medical images. This technique also overcomes the limitation of the existing technique which is applicable on only the Region of Interest (ROI) of the medical image.

IoT-Based Health Services Framework for Endless Ailment Administration at Remote Areas

The objective is to build an IoT-based patient monitoring smart device. The device would monitor real-time data of patients and send it to the Cloud. It has become imperative to attend to minute internal changes in the body that affect overall health. The system would remotely take care of an individual's changes in health and notify the relatives or doctors of any abnormal changes. Cloud storages provide easy availability and monitoring of real-time data. The system uses microcontroller Arduino Nano and sensors – GY80, Heartbeat sensor, Flex sensor, and Galvanic Skin (GSR) sensor with a Wi-Fi Module.