View source for AdviNow, Inc. (20240266055). SYSTEMS AND METHODS FOR AUDIO MEDICAL INSTRUMENT PATIENT MEASUREMENTS simplified abstract

=SYSTEMS AND METHODS FOR AUDIO MEDICAL INSTRUMENT PATIENT MEASUREMENTS=


==Organization Name==

[[:Category:AdviNow, Inc.|AdviNow, Inc.]]


[[Category:AdviNow, Inc.]]

==Inventor(s)==

[[:Category:James Stewart Bates of Paradise Valley AZ (US)|James Stewart Bates of Paradise Valley AZ (US)]][[Category:James Stewart Bates of Paradise Valley AZ (US)]]

[[:Category:Kristopher Perry of Phoenix AZ (US)|Kristopher Perry of Phoenix AZ (US)]][[Category:Kristopher Perry of Phoenix AZ (US)]]

[[:Category:Chaitanya Prakash Potaraju of Tempe AZ (US)|Chaitanya Prakash Potaraju of Tempe AZ (US)]][[Category:Chaitanya Prakash Potaraju of Tempe AZ (US)]]

[[:Category:Pranav Bhatkal of Tempe AZ (US)|Pranav Bhatkal of Tempe AZ (US)]][[Category:Pranav Bhatkal of Tempe AZ (US)]]

[[:Category:Aditya Shirvalkar of Tempe AZ (US)|Aditya Shirvalkar of Tempe AZ (US)]][[Category:Aditya Shirvalkar of Tempe AZ (US)]]

[[:Category:Tristan Royal of Phoenix AZ (US)|Tristan Royal of Phoenix AZ (US)]][[Category:Tristan Royal of Phoenix AZ (US)]]

==SYSTEMS AND METHODS FOR AUDIO MEDICAL INSTRUMENT PATIENT MEASUREMENTS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240266055 titled 'SYSTEMS AND METHODS FOR AUDIO MEDICAL INSTRUMENT PATIENT MEASUREMENTS

The patent application describes systems and methods for accurately acquiring medical measurement data of a patient's body part to assist in diagnosis and treatment.

* Automated diagnostic and treatment system provides instructions to the patient for precise positioning of a medical instrument near a target spot on the body part.
* Utilizes object tracking to ensure the patient has positioned the instrument correctly.
* Uses DSP processing to confirm the instrument is functioning and generate pre-processed audio samples.
* Applies machine learning to detect signals of interest and evaluate characteristics indicating abnormalities in the organ being measured.

==Potential Applications==
This technology can be applied in various medical settings such as hospitals, clinics, and telemedicine platforms for accurate diagnosis and treatment.

==Problems Solved==
The technology addresses the challenge of obtaining precise medical measurement data from patients, ensuring accurate diagnosis and treatment.

==Benefits==
The system improves the accuracy of medical measurements, leading to more effective diagnosis and treatment plans for patients.

==Commercial Applications==
Title: Automated Medical Measurement System for Enhanced Diagnosis and Treatment
This technology can be utilized by healthcare providers, medical device manufacturers, and telemedicine companies to improve patient care and outcomes.

==Questions about the Technology==
===How does the automated diagnostic and treatment system improve the accuracy of medical measurements?===
The system provides instructions to patients for precise positioning of medical instruments, utilizes advanced technologies like object tracking and machine learning to ensure accurate data acquisition.

===What are the potential implications of this technology in telemedicine platforms?===
This technology can enhance the quality of remote medical consultations by providing accurate measurement data to healthcare providers for diagnosis and treatment planning.


==Original Abstract Submitted==

presented are systems and methods for the accurate acquisition of medical measurement data of a body part of patient. to assist in acquiring accurate medical measurement data, an automated diagnostic and treatment system provides instructions to the patient to allow the patient to precisely position a medical instrument in proximity to a target spot of a body part of patient. for a stethoscope examination, the steps may include utilizing object tracking to determine if the patient has moved the stethoscope to a recording site; utilizing dsp processing to confirm that the stethoscope is in operation, utilizing dsp processing to generate a pre-processed audio sample from a recorded audio signal; using machine learning (ml) to determine if a signal of interest (soi) is present in the pre-processed sample. if soi is present, using ml to evaluate characteristics in the signal which indicate the presence of abnormalities in the organ being measured.



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