Smart Health – Potential and Pathways: A Survey

Healthcare is an imperative key field of research, where individuals or groups can be engaged in the self-tracking of any kind of biological, physical, behavioral, or environmental information. In a massive health care data, the valuable information is hidden. The quantity of the available unstructured data has been expanding on an exponential scale. The newly developing Disruptive Technologies can handle many challenges that face data analysis and ability to extract valuable information via data analytics. Connected Wellness in Healthcare would retrieve patient’s physiological, pathological and behavioral parameters through sensors to perform inner workings of human body analysis. Disruptive technologies can take us from a reactive illness-driven to a proactive wellness-driven system in health care. It is need to be strive and create a smart health system towards wellness-driven instead of being illness-driven, today’s biggest problem in health care. Wellness-driven-analytics application help to promote healthiest living environment called “Smart Health”, deliver empower based quality of living. The contributions of this survey reveals and opens (touches uncovered areas) the possible doors in the line of research on smart health and its computing technologies.


Introduction
Medicine is an industry that pays great attention to the accumulation and renewal of knowledge. Connected Wellness in Healthcare is all about retrieving people's physiological parameters through sensors and performing analysis. Disruptive technologies like; IoT, Cloud, Big Data Analytics and Sensing can take us from a reactive illness-driven HealthCare System (HCS) to a proactive wellness-driven system. It is expected that the healthcare costs will account for 20-30% of GDP in some countries by 2050 [1,2]. In order to ensure quality of life for the elderly citizens specialized in HC systems need to be designed that will minimize human wellness centered support systems [3]. In HCS, stakeholders like doctors, care givers, hospitals, pharmaceutical companies, medical device manufacturers, all benefit when the patient becomes ill, should keep patients healthy. Business models are in force towards the HC stakeholders of medical eco-system, when people are not well. There is a need to strive towards a system that is wellness-driven instead of being illness-driven, today's biggest problem in health care. It will help to promote healthiest living environment called "Smart Health" (Collaborative disease management and care coordination) art of diagnostics to science of prognostics, deliver empower based quality of living. This survey reveals and insights the possible doors in the research line of Smart Health and its computing technologies.

Impact on Digital Data in Patient era
The healthcare industry today generates large amount of (both unstructured and structured) data from record keeping of patient related data, health and medical devices related data, drug research data, health insurance data, clinical outcome data, laboratory data, images with graphic, audio, video data, health policy data [4]. The use of health big data (Electronic Health Records (EHRs) already been proven to be effective for a wide range of healthcare challenges, such as disease management support [5], building models for predicting health risk assessment [6], enhancing knowledge about survival rates, discovering co morbidities, and building support systems for the recruitment of patients for new clinical trials [7].

MOTIVATION
Smart Health provides healthiest living environment by way of empowering the quality of life. In massive health care data sets, the valuable information is hidden. Despite some advances, many people yet to have access to affordable and effective healthcare. Significant challenges remain for many patient populations, including the elderly with chronic conditions or diseases. To address these needs, evaluation of models of wellness applications in disease etiology, customize care shift will focus disease treatment to prevention. Connected Wellness in Smart Health is a major uncovered area towards health care system. It is to be harnessed by using big data processing technologies to deliver the right health big data analytics to right living (people) for getting right care (wellness-driven).

SMART HEALTH (SH)
Smart Health provides healthiest living environment by way of empowering the quality of life. Collaborating the disruptive technologies (Internet of Things (IoT) + Cloud Computing + Smart Sensing + Big Data technologies), a paradigm shift in the field of ICT to promote and render right solution, right care coordination in the collaborative management called "smart health". The sensors, devices (mobile phones, surgical devices that measure our blood chemistry and brainwaves), computers, fit bit smart bands, applications, human actors are all Intelligent Agents, might be connected in the Smart Health System (SHS), provide health related services using a network. Simply, SH will connect multiple agents like; patients, devices, networks, providers. SH will integrate various nearby big health care data sources of patient data like, Electronic Health Records (EHR) -stores patient's demo-graphics, medical history, medication and allergies, radiology related information, immunization status, vital organ status, lab test results and personal details on age, weight, height etc.) (e.g

Smart World
The concept of [8] smart world (comprising smart environment (smart health [health tracking-RFID, smart pharmacy], smart people, smart homes and offices, smart plant, smart water supply), smart sensing, smart police, smart transportation (smart cars, smart traffic, smart parking, 3D assisted driving), smart cities, smart homes, smart grids, and smart lights etc.,) is one of the emerging research areas of the 21st century. Smart Robot taxis and City Information Model (CIM) are the futuristic application domains. Concept of smart cities is one of the major areas that is getting promoted and focused is the "Healthiest living environment or smart health" [9].

IMPACT ON ANALYTICS SYSTEM, BIG DATA AND BD ANALYTICS IN HEALTHCARE (BDAH)
In the current age of smart phones, wearable devices and IoT, large amounts of health data files forming "Big Data" are being placed into databases where they can be accessed by multiple users including doctors, caregivers and patients. Big Data Analytics in Healthcare (BDAH) is envisioned to offer big scientific insights that eventually helpful in alleviating the human life and community at large [10]. Diagnosis, Treatment of diseases, and Readmission of patients into hospitals are some of the applications of analytics of BD. Analytics techniques can be categorized into four levels as detailed in Table.1 To predict the probability of an uncertain outcome. (For Proactive care or Lifestyle changes thro' Prediction Models [30][31][32][33][34]).

Statistics and machine learning
Prescriptive analysis To optimize the decision outcomes DT, linear & non-linear promg. Monte-carlo simulation Analytics system can provide the necessary data and evidence-driven prognosis addressing the migration from illness to wellness. India spends around 4.2 % of its GDP on healthcare. It insists that use of big data analytics to bestow better healthcare facilities to its citizen [11]. BDA helps in understanding the data patterns and its relationship with the help of clustering, classification, decision tree, association, sequence analysis, segmentation, regression and data mining, and image processing algorithms.

Role of BD and Data Analytics in Health Care (HC)
Big data and its analytics can help in following areas [11]: Clinical Treatments: It allows efficient storage of both structured and unstructured healthcare data and by performing analytics. Comparative Effectiveness Research can be used to provide optimal treatment to specific patients. Administration: Helps to maintain all the transactional records, financials and will keep the track of EHRs data of patients, feedback and schedule of doctors and nurses to make decisions. Health Policy: Helps to allow governments to make health policy and decide health budget according to the obtained results from large data sets. Clinical research and development: BDA will assist medical students to do research in treatment, genomics, semantic and drug analysis research. Public health: Benefit in tracking infectious diseases outbreak, its pattern analysis and transmission for improving public health surveillance and response. Patient Profile Analytics: To identify individuals who would benefit from proactive care or lifestyle changes. Device/Remote monitoring: Capability of capturing and analyzing the real-time large volumes of fast moving data such as of in-hospital and in-home devices, for safety monitoring [12]. Clinical outcome and safety: In case of emergency & safety, helps in easy access of health record. Fraud Detection: Insurance claim related fraud can be detected and eliminated using big data analytics.

Health Care (HC) Services: Predictive / Proactive
The healthcare services need to be predictive and proactive to limit the occurrence of expensive acute health episodes [13]. HC services need to be individualized, rather than population-based in order to guarantee the delivery of the right treatment. The delivery process of care services need to be decentralized from hospitals to the community and the home. In practice, Information and Communication Technologies (ICT) can play a main role in providing an effective solution to deliver manageable models of patient services in home and community locations.

Levels of HC in India
The rural public health care system in India has three different levels of health care access called primary, secondary and tertiary health care. At the lowest level, Primary Health Center (PHC) which is basic units having minimum facilities serving the rural India, each PHC supervises sub-centers, are most basic units of health in villages and first point for treatment between villagers and public health care. Secondary HC is the second tier of health system where patients from primary health care are referred for specialized treatment [14]. The health centres for secondary health care are District hospitals and Community Health Centre. Tertiary health care is the third level of health system, where in specialized consultation is provided on referral from primary and secondary health care. Specialized Intensive Care Units, advanced diagnostic support services and specialized doctors are the key features of it. In India, tertiary care is provided by either medical colleges or advanced medical research centers [14].

Patient Monitoring
In Healthcare, the most impacted domain is Patient Monitoring, where the taxonomy of IoT based services, detailed in Table 2.

GENESIS OF SH -DISRUPTIVE TECHNOLOGIES (SH= IOT+WSN+CC+BDA)
SH is defined as well-thought-out blend of WSNs-CC-IoT, empowers the quality of living to the fullest extent and could be termed as "Smart Health" [15]. Advances in medicine and clinical care are increasingly tied to computing technologies. It explores emerging trends in smart health and the benefits they bring to individual patients and society as a whole. The rapid expansion of big data analytics and cloud computing technologies has led to the creation of powerful new tools including virtualized tissue banks and disease-specific clinical-trials recruiting and selection databases. Such tools let researchers more nimbly leverage our growing knowledge of human biology to directly improve patients' health outcomes and quality of life. Despite these advances, many people still do not have access to affordable and effective healthcare, and significant challenges remain for many patient populations, including the elderly with chronic conditions or diseases. To address these needs, researchers are designing, implementing, and evaluating novel smart-health and wellness applications to better understand disease etiology and pathogenesis, reduce medical costs, customize care, and shift the focus from disease treatment to prevention. Key ongoing research activities include analyzing physiological and behavioral data from mobile and environmental sensors, improving telemedicine services, and exploiting emerging information sources such as social media and health data aggregators [16].

Role of Internet of Things (IoT)
IoT is defined as"the interconnection of uniquely identifiable computing devices via Internet connectivity among devices, services and system, enable automation in many areas of health care application. IoT is also expected to generate large amounts of data from diverse locations and from heterogeneous sources. When multiple sensors are used together and interact, they are referred to as a Wireless Sensor Networks (WSN). Advances in sensor, wireless communication, and data processing technologies are the driving force for implementing IoT in healthcare systems. The emerging Wearable Body Sensor Networks (WBSNs) were developed to monitor patient activities or medical parameters continuously [17].
Internet of Things" connected devices to almost triple to over 38 billion unites by 2020 [18].

Role of Medical IoT (mIoT)
Devices that constantly monitor health indicators and auto-administer therapies, these devices and mobile apps are now increasingly used and integrated with telemedicine and telehealth via the medical Internet of Things (mIoT). Sensing-based technologies are projected to participate as one of the fundamental contributors to the big data era especially as the Internet of Things (IOT) has started to gain attention in our daily activities [19]. [20] (Refer Table 3)

Role of Sensing Technologies (Wireless Sensor Networks [WSN])
Sensors Technologies can take a main role in developing healthcare services with smart software capabilities. Sensing is a pervasively used technology in nearly every aspect of hospital-based service starting from the simplest digital thermometer to complex laser-guided surgical tools [21]. Sensors are defined as a devices that converts a physical measure into a signal that is read by an observer or by an instrument and "sense" the state of an environment or object, have a significant role in the medical treatment process. Sensors can monitor the characteristics of the environment or objects like temperature, humidity, movement, and quantity. Actuators can affect the environment by emitting sound, light, radio waves or even smells. Sensor Data, exhibits three characteristics of BD: Volume, Variety and Velocity. Sensing technology [21] can play a main role on monitoring the main health status indicators of an individual via ambient monitoring of day-to-day patterns, where in-house healthcare has become a main component of the IOT [22]. Advanced sensing devices are utilized by pathologists in hospital laboratories to perform hematology, immunology, biochemistry, histopathology and microbiology functions.

Role of RFID sensor networks (RSN)
RSN are the possibility of supporting sensing, computing, and communication capabilities in a passive system. RFID systems are the very small size, very low cost and its lifetime is not limited by the battery duration. Implantable sensors [23] address the challenges of both acute and chronic disease monitoring by providing a means of capturing critical events and continuous streamlining of health information. Ambient sensorsand objects interconnected into an integrated IoT represent a promising and supportive solution for the "ageing society".

Role of Imaging Sensing Technologies -Diagnostic Medicine
Evolution of radiology in the use of digital imaging systems, particularly in radiology, where digital management of images has allowed the healthcare department to be more efficient, reduce operating costs, and improve the communication between radiologists and the referring physician. Examples are electronic and Imaging (e.g., Magnetic Resonance Image (MRI), X-rays), Positron Emission Tomography (PET), Computed Tomography (CT), Wave analysis (EEG, ECG), Laparoscopic surgery and ultrasound are commonly used imaging technologies for providing medical insights into the health status of every patient.

Role of Wearable Sensing Technology (Remote, Digital and Mobile Technologies)
Wearable devices are being developed at breathtaking speed [24]. The growing wearable technology can keep track on our bodies' inner workings.These are remote, digital and mobile technologies that integrate with other systems so as to collect, access, and mange patient information (generate smart EHRs). Wearables and mobile apps today support fitness, health education, symptom tracking, and collaborative disease management and care coordination. A new category of "personalized preventative health coaches" (Digital Health Advisors) will emerge. Wearable applications are emerging that could extend the quality and length of life in ways never before thought possible. E.g., of Wearable Devices, e.g., smart shoes, smart watch, smart bracelet, etc., E.g., of Wearable (Medical) Devices, e.g., ECG and respiration, motion sensors, etc.,

Wearable based Physiological Sensing
Wearable devices are expected to lead the next device revolution. These are more capable not only to sense Photoplethysmogram (PPG -signals sense the heart rate, respiratory rate and BP can be measured), signal from a wrist wearable (www.shimmersensing.com) but also get ECG waveforms from it. (www.empatica.com).

Wearable Pathological Sensing
Current pathology systems are invasive in the sense that blood or other in-body fluid samples need to be collected. Future generation pathological sensing either uses easily available outer body fluid like sweat or teardrops. Reports on measuring blood glucose from tear drops [25]. Google announces to build a smart diabetic sensing contactlens using this technology. Another study reported that doing body nutrient analysis using tear drops (www.superiorideas,org/projects/infant-teardrop). Startup organizations aim to build wearable sensors that can sense and analyze body sweat for measuring hydration, fluid loss and electrolytic imbalance and (www.wired.com/2014/11/sweat-sensors) Smart ingestiblepills(www.marsdd.com/news-and-insights/ingestibles-smart-pills-revolutionize-healthcare). Scientists reported that measurement of ethnol, drug, ion and metal content from body sweat [26].

Nearable Devices
It means that camera and RF sensing devices which can be placed near a person to gather information about physiology. No external device or internal implant need to be placed on a person's body. Recent work by MIT which can sense heart rate from normal optical camera signals using 3D image processing tracking micro movements in our face due to blood pumping [3]. Once mature this technology, it would be a low-cost and monitor health of multiple patients without putting anything on patient's body.

6.6.1IoT Smart Health Opportunities and Challenges
Kind of things we can get from IoT are remote monitoring, self-management of chronic conditions, performance improvement, behavior modification, detection & diagnosis and treatment etc., these are platform & data heterogeneity, data integrity & accuracy, privacy, security and trust based challenges.

Bluetooth Technology
Most of the devices use mobile phones as a gateway for transmission using low power protocols like Bluetooth Low Energy (BLE) instead of connecting to the internet directly via a cellular connection. BLE (Bluetooth LE) marketed as Bluetooth Smart, is a wireless personal data network technology marketed by the Bluetooth Special Interest Group aimed at novel applications in HC, fitness, beacons, security, and home entertainment industries. E.g., Classic Bluetooth and Bluetooth Smart.

Wireless Telemedicine & Applications
HC at a distance (Telemedicine [Tele-cardiology, Tele-radiology, Tele-psychology]) relies on the use of telecommunication and ICT. It is essential for HC institutions to invest more into telemedicine. It helps in saving lives during critical situations through technology. Moreover, the worldwide HC services in rural areas still remain as a major challenge [27]. One of the characteristics of "Validity" in Big data can play an important role by making available reports or results using big data analytics in seconds. Since, it refers to time dependent data in healthcare like in telemedicine patient's information of each second is important during treatment. If data reaches late patient's life is at stake. (For example there are certain tests which are locally not possible to detect, than samples are sent to big cities and their reports takes three to seven days in India to give results)

Role of Cloud Computing
Cloud Computing (CC) has been acknowledged on the top of Gartner's list of the ten most disruptive technologies of the next years [28]. CC consists of a front-end (users' computers and software required to access the cloud network) and back-end (various computers, servers and database systems that create the cloud).

Cloud computing in Healthcare
Use of CC in healthcare is emerging [29]. CC enables the use of computing resources and standard mechanisms supported by heterogeneous thin or fat client platforms (e.g., laptops, mobile phones, and PDAs). Cloud is able to provide at-rest analytics (i.e., retrospective analysis) for stored data thro' its delivery models like SaaS (end users to utilize outsourced software) , IaaS (physical environment is outsourced), PaaS (platform is provided) and DaaS (data can be housed within a cloud). Cloud Computing could improve health care services and research [27]. Since, high speed physiological data is an untouched resource in healthcare. BSaaS, PTaaS and BioAaaS are the examples of healthcare related cloud services.

Role of cloud computing for big data
CC and BD paradigm is emerged to address the data-oriented challenges. Communication between the cloud environment and external world is facilitated by the interfaces (like either by GUI or APIs) made available by the service providers. Interfaces provide the users not only rich-set of operations (like; collection, aggregation, visualization and data mining) but also the platforms to perform them, directly by click-based selection or via programming implementations. CC credited (applicability, usability and acceptability potentials) to bring the analysis of big data to the users of various level of scientific and technological understanding ranging from naïve to elite experts.

CONCLUSION
This is a content & computing-rich domain and complex research area that has to be well-positioned to investigate in the health care perspectives. This summarized survey on potentials to smart health, and pathways to disruptive technologies would definitely open eye to inspire and extend the interests in naïve and elite researchers, since upward health care analytics are shaping up the current research efforts in emerging disruptive technologies. This research attempt may survive in 2050.