Examples of medical software and hardware expert systems for dysfunction analysis and treatment

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1 year ago

Examples of medical software and hardware expert systems for dysfunction analysis and treatment

                 A new approach of registering and processing speech characteristics for individuals with central nervous system vascular lesions is presented. Strokes are the most common cause of it, with localized abnormalities of cerebrum functioning induced by vascular damage. The quality of speech is determined by the central nervous system's programming activity and the state of the broadcast of stimuli in the cortical-subcortical region. Voice analysis was carried out utilizing our own signal processing methods based on Fourier transforms. Furthermore, statistical analysis was utilized to establish a reasonable association between the improvement of voice characteristics and the neurological state of the patient under consideration.

                 Several individuals with ischemic and hemorrhagic stroke had the tests done during the first three days of their hospitalization. Following then, the examinations were repeated once a week. The voice analysis of patients with ischemic brain stroke, done using software, revealed distinct abnormalities in frequency and amplitude in the formant parameters when compared to him controls. In the event of a hemorrhagic stroke, the same anomalies were much lower in individuals with aphasia. The technology given here allows for the establishment of a potential of speech recovery process right at the start of the ischemic stroke.

                    During the recording, numerical data are attributed to the patient's state of health and compared to data from a healthy individual of the same age and gender. Analyzing time, frequency, and time-frequency relationships. Because the g-force vector is constant during such a movement, measuring rotation in the horizontal plane cannot be done analogically.Aside from gravity, the Earth is also a source of magnetic field, which may be utilized to estimate the patient's heading using a magnetometer. Any sensor mistake will be incorporated over time, causing the angle value to drift continuously. Furthermore, the integration constant is unknown ahead of time.

                     The gyroscope, on the other hand, is more trustworthy than the magnetometer and is used in the proof-of-concept device. Both concerns mentioned above must be resolved in order to fully utilize the abilities of this sensor. Aside from gravity, the Earth is also a source of magnetic field, which may be utilized to estimate the patient's heading using a magnetometer. Any sensor mistake will be incorporated over time, causing the angle value to drift continuously. Furthermore, the integration constant is unknown ahead of time. The prototype process raised a number of challenges that an engineer would confront when building identical equipment. The most significant limitation is that there are presently no inexpensive MEMS accelerometers with resolutions greater than 12 bits. However, in some instances, its performance may be sufficient, particularly if feedback is delivered using a simulated pointer rather of the actual one.

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