,In 2014 the orthopaedic brace and support market was $3.2 Billion dollars. Knee braces specifically accounted for 42.5% of the market ($1.4B). This enormous figure makes sense considering the approximately 700,000 knee replacement surgeries that are done annually and the 12M annual knee related doctor visits that are made in general.
Unfortunately, current methods of patient monitoring and treatment are time consuming, expensive, and do not extend past the doctor's office. Generally, when rehabing the knee after an injury or surgery patients, will visit their doctor once every few days or weeks. The primary metrics that doctor's measure for a recovering patient are the knee's extension and flexion. These are two anatomical terms describing motion. Extension is the ability of the knee to straighten the leg out to extend a full 180 degrees, while flexion is the ability of the knee to make as acute an angle as possible with the backside of the thigh. High degrees of freedom for these two motions indicate a properly working knee. However, most people cannot easily measure these angles by themselves at home, and thus there aren't many ways to accurately assess patient progress outside of the doctor's office. This lack of data to aid the recovery process can result in poor patient-doctor communication and inefficient recuperation.
Therefore we propose a solution that lives at the intersection of wearable devices and connected health. The emBRACE is a smart knee brace that uses two Broadcom WICED(Wireless Internet Connectivity for Embedded Devices) Sense dev elopment kits to gather information about the knee's movement and position to aid in user recovery. The WICED Sense is a Bluetooth enabled smart sensor tag that can easily be integrated onto everyday objects for quick prototyping. These devices are low cost devices that work on various platforms such as iOS, Andriod, Windows, and PC. The emBRACE specifically utilizes the WICED Sense's accelerometer and gyroscope. An accelerometer is an electromechanical device that measures non-gravitational acceleration. It is good at measuring dynamic forces that cause movement or vibration. Accelerometers can be used for various applications such as inertial navigation systems for aircraft and missiles as well as to induce safety measures in laptops( turning off the laptops hard drive if it measures that the machine is in freefall). Similarly, a gyroscope is a spinning wheel or disc that uses Earth's gravity to determine orientation. The gyroscope has a freely rotating disk called a rotor that when mounted onto a spinning axis in the center of a larger and more stable wheel identifies gravitational pull. The main difference between accelerometers and gyroscopes is that the latter can measure the rate of rotation while the former cannot.
Unfortunately, current methods of patient monitoring and treatment are time consuming, expensive, and do not extend past the doctor's office. Generally, when rehabing the knee after an injury or surgery patients, will visit their doctor once every few days or weeks. The primary metrics that doctor's measure for a recovering patient are the knee's extension and flexion. These are two anatomical terms describing motion. Extension is the ability of the knee to straighten the leg out to extend a full 180 degrees, while flexion is the ability of the knee to make as acute an angle as possible with the backside of the thigh. High degrees of freedom for these two motions indicate a properly working knee. However, most people cannot easily measure these angles by themselves at home, and thus there aren't many ways to accurately assess patient progress outside of the doctor's office. This lack of data to aid the recovery process can result in poor patient-doctor communication and inefficient recuperation.
Therefore we propose a solution that lives at the intersection of wearable devices and connected health. The emBRACE is a smart knee brace that uses two Broadcom WICED(Wireless Internet Connectivity for Embedded Devices) Sense dev elopment kits to gather information about the knee's movement and position to aid in user recovery. The WICED Sense is a Bluetooth enabled smart sensor tag that can easily be integrated onto everyday objects for quick prototyping. These devices are low cost devices that work on various platforms such as iOS, Andriod, Windows, and PC. The emBRACE specifically utilizes the WICED Sense's accelerometer and gyroscope. An accelerometer is an electromechanical device that measures non-gravitational acceleration. It is good at measuring dynamic forces that cause movement or vibration. Accelerometers can be used for various applications such as inertial navigation systems for aircraft and missiles as well as to induce safety measures in laptops( turning off the laptops hard drive if it measures that the machine is in freefall). Similarly, a gyroscope is a spinning wheel or disc that uses Earth's gravity to determine orientation. The gyroscope has a freely rotating disk called a rotor that when mounted onto a spinning axis in the center of a larger and more stable wheel identifies gravitational pull. The main difference between accelerometers and gyroscopes is that the latter can measure the rate of rotation while the former cannot.
The emBRACE then passes the data from the two sensors to an Android App using a Bluetooth Low Energy (BLE) link. BLE is a wireless personal area network technology that is similar to Classic Bluetooth, expect that it operates at a much lower power for a much smaller cost. Several mobile operating systems such as Android, iOS, and Blackberry natively support BLE as do the WICED Senses. The mobile App writes this data to the Amazon Web Services cloud using a regular internet HTTP/S connection. The Amazon Web Services environment (AWS) host a Elastic Compute Cloud where the data is received and stored to a Dynamo Data Base as a relational database. Amazon DynamoDB is a fully managed very fast database service that is convenient to use for mobile and IOT applications.
The preprocessed data goes through a low pass filter and kalman filter, and is then classified using multi-class Support Vector Machines (SVM). While traditional SVMs were originally designed for binary classification,multiclass SVMS build two-class classifiers over a feature vector derived from the pair consisting of the input features and the class of the datum. This processed data is then written back to dynamoDB and then pulled by the web app for visualization. The web application is developed using Bluemix, an IBM tool that allows developers to quickly and easily create, deploy, and manage full stack web applications on the cloud. The web app is beneficial as it provides current and historical visualized data for the user to review.
The preprocessed data goes through a low pass filter and kalman filter, and is then classified using multi-class Support Vector Machines (SVM). While traditional SVMs were originally designed for binary classification,multiclass SVMS build two-class classifiers over a feature vector derived from the pair consisting of the input features and the class of the datum. This processed data is then written back to dynamoDB and then pulled by the web app for visualization. The web application is developed using Bluemix, an IBM tool that allows developers to quickly and easily create, deploy, and manage full stack web applications on the cloud. The web app is beneficial as it provides current and historical visualized data for the user to review.