BME100 f2017:Group7 W0800 L2
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LAB 2 WRITE-UP
Device Image and Description
The device will consist of two sensors. One EKG (ECG) nanosensor (and heartbeat monitoring system) being over the chest to monitor heart rate and variability, and another on the upper back to monitor respiratory information via a possible series of acoustic sensors. The idea is the combination of this cardiac and respiratory information that our device will provide will enable a collection of algorithms set as an app on other devices (such as phones/computers) to generate relevant data and allow preventive action to cardiac and respiratory attacks in patients (such as asthmatic episodes or severe allergic reactions).
Technical and Clinical Feasibility
b. What are the challenges? The size of the device is the most significant challenge. The device needs to use both an acoustic and a heartbeat sensor and have connect-ability to a network for data communication. Similar devices of high accuracy on the clinical market tend to be bulkier, not keeping with the “sleek” wearable technology idea we have in mind (4). It will also include a tracking device in order to provide information regarding the location of the individual in an emergency. 2-3 sensors need to be integrated into a device which should be wearable under regular clothes and not obvious to other viewers. Providing an appropriate connection platform is another challenge associated with the project. Wifi and LTE networks might not be available in all locations; thus, a more reliable network should be provided by providers. The application needs to be able to collect and analyze the data provided by both sensors. These application have been created in the past and have been proven to be successful; however, their creation would require a considerable level of programing skills. Finally, the device needs to stay in place on the human body. Finding the most efficient adhesive material or an appropriate design causes issues as well.
c. What could go wrong? The most important issue with the device is network connectivity. As mentioned earlier, the device needs to have constant connection to network in order to convey information to smartphone for analysis. If a proper network is not available or if connection is lost, the device will not be able to work efficiently. In order to reduce this issue, the device will be able to send an alarm to individuals near the person wearing the device.
It is highly probable that this technology will work. The acoustic respiratory sensor can be programmed to sense specific sound patterns in the patient. To minimize risk of false alarms (incorrectly identifying acoustic signals) parameters can be set for the patient upon acquisition of the device. The device will be able to differentiate wheezing from, for example, talking or eating. The device will also be programmed to detect potential respiratory emergencies. There will be a programmed threshold that will send a push notification warning that the current activity is likely to cause a respiratory emergency. Physiological signals that would be indicative of this are dramatically increased heart-rate and respiratory rate for an extended period of time (1). The second threshold will detect current respiratory emergencies and send a push notification offering an option to ‘contact emergency medical services’ or ‘acknowledge’ which will give the parent/guardian an opportunity to treat the emergency with medication. Physiological signals that would indicate this form of emergency would be excessive breath sounds (wheezing, gurgling, coughing) combined with an increased heart-rate. The third and final threshold will recognize an unconscious/unresponsive victim and contact emergency medical services automatically. The physiological signals associated with this threshold would be lack of breath, cardiac dysrhythmia, or asystole.
There are not many immediate health risks that would come about from this device. There is a chance that the device can be parameterized incorrectly which will result in either false alarms or missing physiological distress signals in the user. A device that only has respiratory sensors has been shown to between 92-95.5% effective in detecting respiratory distress signals. Pairing a respiratory sensor with a cardiac activity sensor can help increase the device’s effectiveness (2),(3). One of the clinical hurdles is the amount of personal data that would have to be collected from the subject in order to obtain accurate and precise information from developed algorithms. Protection for sensitive personal information is becoming more and more of an ethical issue.
Similar products such as MDPI respiratory sensor have gone through clinical trials demonstrating promising results. Masimo, a device that detects respiratory rates in pediatric patients, have been in a clinical trial from 2013 to present. So far they have demonstrated that 39/40 patients respond well to an acoustic sensor and demonstrate accurate results (2).
The device utilizes two sensors in order to notify individuals of their health status and contact proper authorities in an emergency situation. While this technology might be more expensive than other similar devices, it can benefit customers in various ways. First, the usage of two sensors increases the accuracy of measurements; thus, providing valuable information to customers. Secondly, the device can be used for patients with asthma or cardiovascular diseases. Finally, both sensors will be closely connected to the heart and lungs which makes the device much more efficient than others in the market.
~89.65$, the cost of making the device is $17.93, so the sales price should be about 5x the cost. The cost of a data plan or a smartphone is not considered in this calculation under the assumption that the average consumer will already have these.
(18.4 million adults + 6.2 million children + 84 million people with coronary heart disease) = 108.6 million people that COULD use our product. When the probable penetrance (5%) is taken into account the number of people that are likely to use this product turns out to be 5.43 million.
Fundability Discussion and Scores
The group has given itself an overall fundability ratings as follows:
Competitors: 2 (lab 1)
Customer Validation: 1 (lab 1)
IP Position: 2 (lab 1)
Market Size: 2
The market size for this product deserves a 2 because its projected to reach about 486 million dollars per year. This is a mere 14 million away from reaching a market size score of 3, so the group will work on finding another demographic group that this product can apply to. It is believed that this product can be useful for a wide variety of people due to the extremely high rates of asthma and cardiac disease in the US.
Technical Feasibility: 2
A score of 2 properly demonstrates how this product can be made by simply placing a few sensors in a waterproof casing and adhering them to the user. The band connecting the sensors will be resistant to bending therefore applying the necessary amount of pressure to take accurate readings. The difficult part of bringing this project to fruition will be to properly code a software with the appropriate differentiate between specific physiological thresholds.
Clinical Feasibility: 2
As mentioned above, the main hurdle for this project will to be to mark distinct physiological thresholds that the software will be able to analyze the patient's needs. However, the efficacy of the these types of sensors are showing promising results within the most recent clinical trials. With recent findings from the sources listed below, it is believed that this device deserves a score of 2 for clinical feasibility.
Determination of Overall Fundability: 32
The fundability score turned out to be a 32. We believe that this score is mainly derived from the fact that we genuinely felt that none of our criteria (competitors, IP position, market size, technical feasibility, clinical feasibility) were able to be considered a score of 3 following to the descriptions of the fundability worksheet provided.
Competitors is scored a 2 because while better options are still being sought, there is still a significant number of similar devices that have similar value and function.
Customer validation was a given as a 1; however we would like to note that given the possibility this score could have been higher given the value of the information this device would accurately and readily provide.
IP position was given a 2 because we did not find a plethora of issued and successful IP patents, and furthermore our device encompassed similar technologies to those successful patents we did find; given this IP position situation we did not feel that a 3 was suitable.
Our market size was deemed a 2 as well because it was just short of 500 million, so close in fact that we were tempted to mark it as a 3, however our logic was that it is better to undershoot your market size than to overshoot it when developing a product; thus we went with the former.
Technical feasibility was given a 2 because while the physical technology is definitely ready, a large part of this device would encompass precise and highly sophisticated analysis of the collected user information, which would require an intense amount of complex coding algorithms.
Clinical feasibility was also given a 2 for a similar reason being that the data collection of clinical trails would not be hard to come by, however the amount of individual biometric information required for the development of the complex software algorithms the device will utilize during these trials is significant and would take a modest amount of time to develop.
Lastly, we would like to note that this project was limited in the fact that regulatory pathway, customer validation, and reimbursement were given to us as a score of 1; had we been able to assess these three criteria our score might have increased considering our device and its noninvasive nature.
(1) MyDr, Bronchial Asthma and Cardiac Asthma, January 2010. Accessed September 2017. http://www.mydr.com.au/asthma/bronchial-asthma-and-cardiac-asthma
(2) Masimo, Accuracy of Acoustic Respiration Rate Monitoring in Pediatric Patients, 2013. Accessed September 2017 http://www.masimo.com/globalassets/pdf/clinical-evidence/acoustic-respiration-rate-rra/patino-accuracy-of-acoustic-respiration-rate-monitoring-in-pediatric-patients-2013.pdf
(3) US National Library of Medicine National Institutes of Health, Multimodal Chest Surface Data for Respiratory and Cardiovascular Monitoring Applications, April 2017, Accessed September 2017, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5404625/
(4) “Respiration Sensor.” Mind Media: Neuro and Biofeedback Systems, http://www.mindmedia.com/products/sensors/respiration-sensor/
(5)Chang, Daniel. “Carbon Dioxide Nanosensor and Respiratory CO2 Monitors.” Google Patents, Google, 1 Mar. 2007, http://www.google.com/patents/US20070048181.
(6) Telfort, Valery, et al. “Acoustic Respiratory Monitoring Sensor with Probe-off Detection.”Google Patents, Google, 24 Nov. 2015, http://www.google.com/patents/US9192351.
(7) “ECG vs PPG for Heart Rate Monitoring: Which Is Best?” NeuroSky, NeuroSky, 28 Jan. 2015, http://www.neurosky.com/2015/01/ecg-vs-ppg-for-heart-rate-monitoring-which-is-best/.
(8) “BMD101 CardioChip.” ECG: BMD101, NeuroSky, http://www.store.neurosky.com/products/ecg-bmd101.