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Significant features of the ECG signal include the P wave, the QRS complex, and the T wave. This paper focuses on the detection of the QRS complex. A 1 st order Gaussian derivative function has a similar shape to QRS complex part of the ECG. In this paper, an FIR filter bank is efficiently designed with lattice structures for QRS features extraction, using Gaussian function with standard deviation value. ECG features are taken after three-level decompositions of the proposed filter bank. Significant energy values of the filter bank output coefficients are calculated and treated as crucial points for identification of the diseases/disorders in the ECG signal. Such values are used for the design of a rule-based fuzzy classifier.

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Any robot system consists of mechanical and electrical components. These components are combined and compacted together with a special controller to do a specific work. Mostly and with time obsolescence, faults and errors are happen in robot systems lead to work problems. Many years ago, researchers are working in this field. In this paper, a review study focuses on this field is introduced to make classifications between different types of faults and diagnosis methods those used in the field of robotics. Many types of faults are studied, according to some previous and recent works. The most detected faults can be classified into two parts: hardware and software faults. The hardware faults part is further classified into two main types; the first one is represented in sensors and actuators, while the other is included taking into consideration both position and velocity in joints. These joints which usually connect the links of the arm with each other and ensure contentions to motors, controllers, and many sensors, are really represent the most important side have to be studied. The software faults part includes those errors occurred during programming such as any error happen in signal translation, signal classification or signal identification is considered as a software fault. In this paper most of the fault diagnosis and detection methods of faults types in the field of robotics are studied. According to these studied papers, the hardware fault part is the most important part which must be identified and corrected in real time using smart methods.

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