## 3 AB Broker Design for Interoperability  
The AB Broker proposed in this paper secures interoperability by developing algorithms developed in different environments in an integrated environment. The use of AB Broker is expected to improve the reusability of various algorithms and provide time for algorithm development. In this paper, AB Broker was developed to secure interoperability between MATLAB, which is conventionally used for algorithm development among various algorithm development tools, such as Python, MATLAB, and R Programming, and open-source R Programming. The application of AB Broker is not limited to only vital sign analysis. In this paper, the proposed approach is the first of its kind developed for vital sign analysis. However, this framework is applicable for other frameworks because it is a generalized framework and there are no restrictions. As shown in Figure 1, AB Broker consists of an algorithm search, algorithm specification agent, execution agent, Algorithm Block Registry (AB Registry), and AB Adapter. * Algorithm search searches for an algorithm to be executed. * The algorithm specification agent checks the information on the algorithm to be executed and displays information on the type of development tool, the input value, and the output value required for execution. * AB Registry is a repository for storing algorithm source files. It has the algorithm source file to execute the algorithm by searching for the algorithm that AB Broker requests to execute. Figure 1: Algorithm Block (AB) broker diagram consisting of search, specification agent, execution agent, and AB adapter. AB Adapter has a service that stores information to call R programming functions in MATLAB and a service that saves information to call MATLAB functions from R programming. The information for executing functions is composed of parameters having the name of the function to be executed and an input value. * Execution Agent executes the algorithm requested by AB Adapter. Algorithm execution has four steps. First, the presence of an algorithm is checked through algorithm search. Second, the algorithm function source is checked in the AB Registry. Third, the input and output values are checked according to the algorithm specification. Fourth, the algorithm is executed by inputting an input value to the algorithm function. The algorithm search and algorithm specification agent analyze data using algorithm information. Algorithm information is stored in the algorithm information database shown in Figure 2. The algorithm details Table stores information on developer ID, algorithm file name, vital sign analysis algorithm explanation, vital sign type, date sent, and vital sign development tool. algorithm_inp_out stores information on input values, input parameters, and input values. The structure of AB Adapter is shown in Figure 3. MATLAB Adapter and R programming Adapter request information to execute functions in MATLAB and R Programming. The working principle of Algorithm Block Broker is shown in the Figure 4. AB Broker requests execution of functions developed in MATLAB or R Programming from AB Adapter. AB Adapter sends information for the execution of the algorithm to the Broker object. The Broker searches for a function in the AB Registry according to the function execution service request. The searched function checks information on the function of the algorithm specification agent. The accurate input and input value required for the execution of the function are checked according to this information. Then, for the function developed in R Programming, the R Programming function is executed through the Java/R Interface (JRI) in MATLAB and the result value is sent to MATLAB. In addition, for the function developed in MATLAB, the MATLAB function is executed through Matlabcontrol, and the result value is sent to R Programming. Figure 2: Algorithm specification table modeling: 1� is a table defining algorithm information; 2� is a table that defines the input and output values of the algorithm.