The “five A’s” were set through an analysis of relative data. A hospital-grade 12-lead electrocardiogram machine, the gold standard of detection technology, is able to provide a definitive diagnosis 90% of the time, so an improvement should ideally be able to match if not exceed this accuracy (“How Is Heart Disease Diagnosed?”, 2014). Similarly, an electrocardiogram test takes five minutes to complete, so through autonomous administration, it would be viable for a consumer device to conduct its own test within less than twenty minutes of the start of a heart attack (acceleration) (“How is Heart Disease Diagnosed?”, 2014). The performance-based aspects of accuracy and acceleration in a device would be most important to a successful detection process, so any design that did not meet the baseline specifications in these two “As” would be inadequate. In the case that a heart attack was detected, the device would then need to be alert and communicate the results with both the user and paramedics to complete a successful detection process. Of course, as a consumer device, it would have to be relatively affordable, so it should be priced at less than $1000 based on current models on the market. Last of all, the comfort and style of the product was crucial to appeal to the customer. These “five As” thus served as a set of quantitative parameters to test which technologies and resultant product designs would have the desired specifications.
B. Product Concepts – Biomarkers:
In order to detect a heart attack, the consumer device would need something tangible to detect, so the first step was to find an indicator tied directly to the condition of the heart. The main alternative to electrocardiography, which tracks electrical signals throughout a heartbeat, seemed to be the numerous biomarkers which change from the norm during a heart attack. None of our product designs tracking these biomarkers ultimately proved to meet the need specifications. However, these failed designs proved to be paramount to the research process, as they eliminated all imperfect solutions to progressively narrow the search for the final answer. An overview of these biomarkers are listed below:
The protein troponin is found in the heart muscle and is released when the muscle takes damage. Thus, during a heart attack, troponin levels exceed the 99th percentile of values (Mahajan and Jarolim, 2011). Two potential product designs were formulated to track changes in this indicator. Inspired by nanotechnology research done by the Vascular Biotechnology Institute, the first design was a pill which would break down into nanoparticles on consumption and collectively report data on troponin levels to a metal wristwatch through magnetic attraction.(“Nanotech Delivers Clot-busting Drugs to Heart Attack, Stroke Patients”, 2015). The second design played with the idea of a blood test self-administered by the patient (“Troponin Test: MedlinePlus Medical Encyclopedia”, 2016). However, it became apparent that both products would be expensive (fail affordability) and had the fundamental flaw of not being able to autonomously track troponin levels (fail alertness). Therefore, none of these products seemed to be ideal. A bit more research revealed that any troponin-based solution could not possibly meet the baseline parameters, as troponin levels themselves spike anywhere from two to six hours after the initial onset of a heart attack (fail acceleration). A test used to track them would take even longer, by which time it would be far too late to save the patient.
White Blood Cells:
As the body’s defense mechanism, white blood cells are called into action to displace the plaque from the blocked coronary artery during a heart attack (Harvard University Staff, 2005) This change from the norm spawned the concept of a surgically implanted chip that could detect elevated levels of white blood cells in the heart. Aside from the fact that chip would be too invasive, the biomarker it tracked was once again unsuitable. White blood cells also spike in a delayed reaction, once again falling short of our needs.
Similar to white blood cells, platelets congregate at the plaque blockage to form blood clots (Kulick, 2015). This reaction is almost immediate and changes in platelet count is thus able to be tracked in time unlike other biomarkers. However, the reaction is unfortunately too localized to track with a great deal of accuracy. Furthermore, the detection method itself, called light scattering technology, is technologically difficult to incorporate into a consumer device and is excessively expensive. These failed experiments in the realm of biomarkers left no choice but to explore the already
saturated field of electrocardiography.
C. Product Concepts – Electrocardiography or Echocardiography?:
With so many consumer devices incorporating ECG technology, a novel product would have to find some way to differentiate itself from the rest. As stated previously, the gold standard in detection technology is the 12-lead ECG, which uses ten electrodes placed across the body to capture twelve different pictures of electrical activity in the heart muscle. These twelve data points provide physicians a perspective from all three planes of motion (sagittal, frontal,
transverse) and thus the accuracy of the diagnosis is ensured (“12-Lead ECG Placement”, 2014). Now, an interview with Dr. Jeffrey West, a practicing cardiologist for twenty years, revealed that most existing solutions replicating this model are fast, cheap, and accessible but sacrifice much of the accuracy of the 12-lead ECG for the sake of these qualities. AliveCor’s Kardia incorporates a 1-lead ECG into an iPhone case to provide readings on electrical impulses in the heart at the touch of a finger (AliveCor, 2016). However, Kardia’s single lead can read data from only one plane of motion and thus has the scope to miss abnormalities in any one of its many blind spots. This is not to mention that Kardia cannot autonomously administer the test. The patient would only check with Kardia if he/she felt any physical symptoms which, as stated before, evolve too late in the process. It thus loses out on not only accuracy but speed, failing both performance-based need specifications listed. iRhythm’s Zio Patch ($299) uses a 3-lead ECG to track electrical activity over a two-week period and thus has higher accuracy, but has little to no ability to detect a heart attack as the data can only be analyzed retrospectively by a physician (iRhythm, 2016). HealthWatch’s ECG Shirt ($199) is the best solution in the market as of now. It integrates electronic leads into the fabric of an undershirt and thus ideally has the accuracy and speed of a 12-lead ECG (Comstock, 2014). An assessment of the competition spawned the product design for the ECG Waistband ($149), a wrap-around wearable which would autonomously scan the heart muscle every half an hour and report and abnormalities to medical authorities. However, this design barely offered an improvement on the ECG Shirt, a device already in the market.
In a second interview, Dr. West thus recommended a closer look into an improbable solution, echocardiography. An echocardiogram uses ultrasound technology to visually study the ventricular motion of the heart (“What Is Echocardiography?”, 2011) During a heart attack, this motion is impaired as the contractile force of the heart progressively weakens due to the lack of oxygen. Echocardiography is at best used in the hospital setting as an alternative test to electrocardiography and is not even considered by the wearables market. Even if one managed to
integrate bulky ultrasound technology into a consumer device, the returned data (body images) would need to be comprehensively analyzed by an expert due to their qualitative nature. If the device scanned and sent results to the hospital every half an hour for inspection, the process would waste medical/human resources, exponentially raise health care premiums for the patient, and kill valuable time which could be the difference between life and death. It would thus be an entirely unrealistic solution in its present state. However, if an echocardiograph could convert
qualitative results into quantitative, machine-readable data, it could potentially yield a viable solution. This road led to the blueprint of a continuous wave Doppler ultrasound patch which would not only advance the heart attack detection market, but also manage to match if not exceed the functionality of the ECG Waistband.
The final product design, a continuous wave Doppler ultrasound patch called the Ekko Patch, has two main components that cooperatively work to provide a diagnostic using a value called the dp/dt max. This stands for the rate of change of ventricular pressure, which is an accurate, quantitative indicator of the contractile force of the heart at any given time. The standard interval used to calculate change in each value is that between the blood velocities of 1 m/s and 3 m/s, which represent those at the beginning and end of a contraction. The change in pressure in this interval is given to be 32 mmHg, but the change in time can only be solved for through the inputted information, which is where the device comes into play (“Ventricular Contractility Assessment (dP/dt))”, 2013). To start the scan every half an hour, a battery pack sends voltage through to the bottom part of the patch, a transducer. This electrical energy is converted to vibrational sound energy as it passes over piezoelectric sensors, thus emitting high-frequency ultrasound waves over the mitral regurgitation jet, a valve located above the left ventricle (“Mitral Valve Regurgitation”, 2016). Due to the Doppler effect, the frequency returned to the transducer changes based on the velocity of the blood. The recorded frequency is then sent up to the top part of the patch, the machine. A processor coded with MATLAB uses the frequency to calculate the blood velocity throughout a contraction and can therefore log the time between the velocities 1 m/s and 3 m/s, thus completing the dp/dt max calculation. The machine accesses the particular patient’s normal dp/dt max range (generally 1000-1200 mmHg/sec) stored in a memory chip. During a heart attack, blood velocity changes at a slower rate in the mitral regurgitation jet due to less contractile force, thus increasing the change in time, and decreasing the dp/dt max evaluation. Therefore, if the dp/dt max reading is 100 mmHg/sec or more below
the low in the normal range, then the patient is at danger. In this case, the machine connects to a wristband via Bluetooth, which then vibrates vigorously to alert the user and autonomously sends a report of the patient’s location to paramedics.