Diabetic Neuropathy is a condition often found in diabetic patients. Nearly 60-70 percent of diabetic patients suffer from some form neuropathy. Patients suffering from neuropathy can often lose sensation within various parts of their body, but not limited to the hands, legs or feet. In particular, neuropathy is found very commonly in the feet. This means that these patients are unaware of what they might be stepping on, and unaware of the amount of pressure they apply to each foot. This leads to complications such as blisters and ulcers.
Our project aims to aid patients lessen the severe effects of neuropathy in the feet and improve the healing process for those with complications caused by neuropathy(i.e. ulcers, blisters, abrasions). Our project does this by collecting real-time foot pressure data on various parts of the feet and offering tactile feedback on the forearm to help a patient orient his weight differently to prevent excessive pressure at any points. This approach will reduce the number of foot ulcers a neuropathy patient may develop, in addition to helping the healing process.
The system consists of two vibrating motors, a spark core, and two force sensitive sensors on both sides of the foot arch, though more can easily be added, and a user interface (mobile/desktop website).
Our system can be setup to warn the patient when they place too much pressure near an ulcerous area. In order to warn the patient, the system will flash an alert on either the mobile or desktop interface. In addition, there are two vibration motors that are worn on a wristband. The motors work independently of each other, one placed higher than the other, to denote posterior and anterior of the foot region. Based on where the pressure is placed, one of the motors will buzz to denote where the patient must shift his weight. Therefore the patient can reliably know how and where to apply pressure to his feet when walking in an effective manner. Thus helping him heal quicker and prevent future ulcers.
The data from the actual sensors is being sent out to the armband and then from there pushed to the cloud. From there, it is processed onto a graphic interface. We have made a web implementation, designed to be scalable across multiple platforms, to showcase the data. It can show the patient the amount of pressure they are putting on each position in their foot, along with a graphical representation of the current pressure (transparent green to opaque red). It also shows the average pressure, for the patient to monitor themselves over a period of time. Eventually, as data accumulates, the circular graph will make it more evident to ultimately know how evenly a user is distributing weight. The webpage can also flash alerts to notify users of an imbalance. This data can also be sent to a doctor's office to monitor patients with more efficiency.
In the future, we plan on adding better and more accurate sensors to get greater precision when creating foot pressure maps. With some more backing, we could also integrate our DIY sensor technology into the sole of the shoe itself, remove the wires running from the sensors to the armband and create a better mapping algorithm. We are also researching the potential of creating better sensors that will also be able to perform accurate weight tracking of a patient, another useful dataset for patients.
Caution! A few values in the source code are calibrated specifically for these sensors, which were made using DIY materials for this particular project. The values given are good estimates and indicators of pressure change, but they are not comparable to the accuracy nor precision of more advanced hardware.