Hospitals are also moving away from purchasing point solutions and toward buying equipments from different vendors that are interoperable, and that have a uniform user interface. Hospitals are developing internal networks that connect all diagnostic equipments, which feed all patient information over a network to data storage servers, for instant access.

Majority of the population needs common diagnostic services to monitor their health data for common diseases of the world. Primary medical diagnostics will be (i) height, weight of the body, (ii) heart beat, (iii) blood pressure, (iv) blood test, (v) body fluid tests, (vi) cholesterol test and (vii) body temperature. Presently medical diagnostics equipments are entering the market as digital embedded equipments, resulting in good accuracy in diagnostic process. Reduced size and display features are making these products flexible, which is facilitating the common men to use them
with ease.

Introduction

The galloping development of the computer and of information technology has made it possible to gather, store, and analyze huge amounts of data, thereby profoundly transforming research in numerous fields. Emergence of mobile cellular phones and embedded hardware has made miniaturization a happening reality.

Lakhs of rural villages in the world have no access to any medical support systems to save their life�despite emerging technologies this is happening due to yawning disparities of income levels and other societal issues. But now healthcare accessibility to remote areas can become possible due to advent of mobile cellular wireless communication. Embedded hand-held mobile medical diagnostics tool will facilitate medical diagnostic need at remote places; for the aged population, and would contribute to reduction of individual medical expenditure. Furthermore, there is no denying the fact that the global healthcare market is influenced by a number of demographic trends, including the following:

�Growing and Ageing Population: The U.S. Census Bureau predicts that the majority of the U.S. ‘baby boom’ population (28 percent of the total U.S. population) will begin to turn 65 between 2010 and 2020;

�Consumer expectations for improved healthcare are increasing in both developed and developing countries.

�The above market projections are also a cause for introduction of innovative medical tools into the healthcare industry.

Emerging Trend of e-Diagnosis

In the next ten years, the healthcare market will focus on early diagnosis- digitized patient information that can be accessed from numerous locations, and ‘total solution’ selling that contributes to healthcare productivity gains. Early diagnosis and prevention is enabled by emerging diagnostic technologies. A ‘paperless’ hospital is another emerging trend. Digital patient records enable doctors to access patients’ records�wherever the doctor is. In a digitized hospital, healthcare providers do not have to wait days for an X-ray to ‘come back from the lab’ because the X-ray machine is digital and the image is instantly available.

Hospitals are also moving away from purchasing point solutions and toward buying equipments from different vendors that are interoperable, and that have a uniform user interface. Hospitals are developing internal networks that connect all diagnostic equipments, which feed all patient information over a network to data storage servers, for instant access. This drives medical equipment vendors to develop interoperable equipments, which have a uniform user interface. In effect, vendors are beginning to sell complete solutions that include not only the diagnostic equipments, but also the data storage servers as well as the interface software.

All these trends are leading to an increase in healthcare productivity�this means more patients can be put through the healthcare system by using better, faster diagnostic equipments, which leads to early diagnosis of ailments and subsequent treatment. When the paperless hospital becomes a reality, productivity would be further enhanced because of instant patient test results and records access. Here in this article, we attempt to give a conceptual idea for a hand-held mobile diagnostics tool, which will integrate all medical testing features in a single equipment, along with integration of mobile communication, for a speedy suggestion from a doctor. The market for these types of products is doubling every year with an inclusion of various features in a single system.

Product Specification and Pre-generation

(i) Component Overview-Concept I

Concept I is about integration of all available digital equipment modules into a single system. The integration will be done with a SBC /Controller based PCB which is integrated with a LCD screen to monitor the displayed data. The centralized SBC will process the total incoming data through various interfaces, and in turn calibrate and display the required values on to the display according to the customized MMI interface.

The displayed data can be accessed through a cell phone and can be transmitted to the predefined receiver; the doctor will use this data and reply back with a medical transcription according to diagnosis results received through wireless transmission. This implementation requires purchase of available components as separate entities and finding interface possibility of different equipments. This diagnostics tool is not suitable for usage as a personnel utility. This can be installed as a system similar to ATM machines at villages or at public places with flexible medical utilities for diagnosis. The main display will act as a man- machine interface with all the alarms and status signals, along with measured/monitored data. Concept I has dependency on external supplier for the purchase of building blocks. The module will occupy more space and will be costly for usage.

Risks in realization of Concept I as a product:

�Finance: For releasing this product in the market huge design and developmental resources should be used, drawn from different areas of electronics domain. This can be developed from governmental sponsorship as the product can be advantageous for the rural areas.

�Availability of digital meters with needed interfaces

�Integration issues for different instruments

The risks have mitigation plan, once the total concept architecture is planned with a dedicated resource for implementation.

Instead of dedicated centralized processor, a desktop PC can be used with its standard interface selection, through a pluggable card for the system. PC/laptop can be connected with wireless network for an instantaneous remote health data monitoring.

(ii) Concept II-Diagnostics Tool Integrated with Cell Phone
To realise this mobile equipment, we require miniaturization of all the processes used for diagnosis, which will be costlier at the preliminary design stages. Any electronic costing depends on the volume of production. This proposed product sure has greater market scope and hence it can be safely expected that the cost of each internal component will be reduced within five years of the first release of the product. The second concept is looking at miniaturization and integration of the entire gamut of medical diagnostic tools into a mobile phone. The purpose is to introduce an innovative medical product into the market with more usefulness to the mobile cell phone user.

Common medical diagnosis can be achieved with smart sensors, which can convert medical inputs into electrical signals and transmit them through a pluggable cable to the multichannel analog input, placed inside the mobile phone.

Processor will digitize the incoming data and process according to the required commands received from cell phone keypad and menu. The processed data can be stored into the memory with date wise file and can be transmitted to the corresponding consulting doctor as a data file, using address book of the cell phone.

However, we must remember that to integrate all equipments into mobile phones requires permissions from medical agencies and doctors, along with calibration certificates from various agencies according to the market geography.

Risks involved in implementation of this system will be-

�Costs to translate the system from concept to reality;
�Complexity of miniaturization;
�Complexity of inclusion of BP machine inside the mobile phone;
�Probes and interface selection and integration;
�Power supply dependencies due to increase in complexity of normal phone function;
�Mixed signal design with RF integration.

Examples of Miniaturized Realisations of Some Medical Diagnosis Equipments

(i) Blood Glucose Tester

Of the two types of test methods used in meters today�electrochemical and light-reflectance�the more commonly used method is the light-reflectance method. With this method, the blood sample reacts with a substance on a test strip so either there’s a colour change based on blood glucose content or it will exhibit certain properties when illuminated by a specific wavelength of light.

In meters using the light-reflectance method, the test strip is illuminated by a light source in the meter, usually an LED emitting in the visible range. The intensity of the light reflected back from the test strip is read by an optical detector, amplified, and converted before being fed to a microcontroller for processing. Great care is being taken to limit the amount of ambient light seen by the detector, since any ambient light is considered noise and reduces the meter’s accuracy.

The desired measurement depends on how the test strip’s chemistry is designed to react with the blood sample. You might want the reflectance of a particular wavelength of light, which can be achieved by either limiting the light source to only that wavelength or by filtering the sensor to see only the wavelength of interest. There are advantages and disadvantages to both of these approaches. Limiting the wavelength means that more is spent on the LEDs to get a particular wavelength output, but it allows you to use a general-purpose detector. Filtering the sensor lets you use a less expensive light source and spend more on a filtered detector, such as the TSLR257, TSLG257, and TSLB257 from TAOS, which are light-to-voltage converters with integrated red, green, or blue filters, respectively.

If you require spectral information from the strip, the approach is to use LEDs tuned for specific wavelengths with tight tolerances. The drawback is that the LEDs may be more costly and there must be a separate LED for each wavelength of interest. If you want to measure a change of colour in the strip, then you can measure the intensity of one or all of its tri-stimulus RGB colour components. If only one colour component is needed, then a light-to-voltage converter with an integrated colour filter for red, green, or blue, respectively, would be the best. In most cases, it is desirable to measure the intensity of all three RGB components. Traditionally, this has been done using photodiodes with RGB filters and discrete components (see Figure 3).

The colour-filtered photodiode outputs are fed to a multiplexer for selection of the red, green, or blue light-intensity data. These data are converted from analog to digital and sent to a microcontroller. A next-generation colour sensor that converts light intensity directly to a pulse train with a frequency proportional to the intensity of the red, green, and blue components, is now available from TAOS. The output of the TCS230 can be fed directly to a microcontroller, eliminating the need for external amplifiers, multiplexers, and A/D converters (see Figure 4).

(ii) Thermometer

Usage of DS18S20 or other temperature sensor in the probe will generate electrical signals, which can be interfaced with the microcontroller /processor module sitting inside the mobile equipment.

(iii) BP Meter

It is based on a digital blood pressure meter concept, which uses an integrated pressure sensor, analog signal-conditioning circuitry. The sensing system reads the cuff pressure (CP) and extracts the pulses for analysis and determination of systolic and diastolic pressure. This design uses a 50 kPa integrated pressure sensor (free scale semiconductor, Inc.P/N: MPXV5050GP), yielding a pressure range of 0 mm Hg to 300 mm Hg. This method is employed by the majority of automated noninvasive devices. A limb and its vasculature are compressed by an encircling, inflatable compression cuff. The blood pressure reading for systolic and diastolic blood pressure values are read at the parameter identification point.

The simplified measurement principle of the oscillometric method is a measurement of the amplitude of pressure change in the cuff, as the cuff is inflated from above the systolic pressure. The amplitude suddenly grows larger as the pulse breaks through the occlusion. This is very close to systolic pressure. As the cuff pressure is further reduced, the pulsation increases in amplitude, reaching a maximum and then diminishing rapidly.

The index of diastolic pressure is taken where this rapid transition begins. Therefore, the systolic blood pressure (SBP) and diastolic blood pressure (DBP) are obtained by identifying the region where there is a rapid increase and then decrease in the amplitude of the pulses respectively. Mean arterial pressure (MAP) is located at the point of maximum oscillation. Other medical diagnostic equipments can be realised similar to the above-mentioned given examples with needed sensors and calibration methods for analog signal conditioning circuitary. New diagnostics features also can be implemented due to integrated centralized monitoring display. However, accuracies of sensors and size will drive the cost of the product.

Conclusion

The primary focus in the development of this tool is to deliver a system, which is configurable and flexible, along with saving of development and maintenance efforts.

This system would be useful for all age groups. Especially old aged people during travelling can have access with their consulting doctor, using their mobile diagnosis utility.

Implementation will take approximately one-and-a-half-year time including integration of the overall system. In the ever increasing miniaturization of electronic equipments and the growing need for accurate and mobile devices, products similar to this integration will create new markets in the medical equipments’ sector.

References:

1.www.edn.com
2.https://www.sensorsmag.com/sensors/
3.https://www.freescale.com/files/sensors/doc/app_note

Intel’s Embedded Digital Solutions for Healthcare

Intel’s Digital Health Group (DHG) aims to improve the health experiences of senior citizens while driving down cost by researching technology that can monitor patients’ health unobtrusively by various sensors embedded throughout the home.

The Technology Research for Independent Living (TRIL) centre, opened in Ireland in January, is part of this initiative and has already begun clinical trials of Intel’s healthcare technology.

“A global demographic tsunami is in the making as elderly citizens look set to reach two billion in the next few decades, according to Eric Dishman, senior official with Intel’s Innovation Centre in Leixslip, Europe. Already EU healthcare costs 30percent of the average GDP, and this is not sustainable.

Dishman says a paradigm shift in elderly healthcare is happening mainly through technological innovation that is mostly wireless and scaleable.

Drawing a parallel with the advent of the home computer, Dishman says this “shift left” strategy could be introduced to the healthcare sector by bringing monitoring equipment to the home. Rather than paying roughly 4,000 euros for an electrocardiogram (ECG) monitor for research purposes, universities and research centres can avail of Intel’s SHIMMER technology. Sensing Health with Intelligence, Modularity Mobility and Experimental Reusability (SHIMMER) ECGs are lightweight, Bluetooth-enabled monitors.

They can track the motion and gait of patients in an effort to better understand and prevent falls, which often lead to rapid health deterioration among the elderly, and can be modified and applied to many areas of ageing research. With open source software and reusability, Intel has already run workshops for universities and TRIL is using its motion sensing technology to run a study of 600 patients in St. James Hospital, Ireland with 2.8m in funding from the Industrial Development Authority (IDA) and Intel combined.

DHG also hopes to create efficiency in the hospital environment by making paperwork and monitoring easier for nurses and doctors. The time spent on caring for patients is often taken up filling in and finding files. The Mobile Clinical Assistant (MCA) is one of the first technologies developed within the DHG. Designed by Intel and produced by Motion Computing, the MCA is waterproof and fall tolerant.

Launched in February this year, MCA is expected to be commercially available very soon. With Bluetooth technology, a built-in camera, RFID reader and software to track inventory and other electronic records, the MCA endeavours to add to workflow efficiency in a hospital environment.

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