Cervical vertebra state recovery evaluation method and system based on deep learning

The invention belongs to the field of cervical vertebra recovery, and particularly provides a cervical vertebra state recovery evaluation method and system based on deep learning, a temperature control cervical vertebra traction instrument applied to interactive communication and a user terminal, an...

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Bibliographische Detailangaben
Hauptverfasser:	GAO QIAOGE, ZHU WEI, TAI MIAO, YANG LIXUE, SUN XIAOJIE
Format:	Patent
Sprache:	chi ; eng
Schlagworte:	BANDAGES, DRESSINGS OR ABSORBENT PADS CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DEVICES PROVIDING PATENCY TO, OR PREVENTING COLLAPSING OF,TUBULAR STRUCTURES OF THE BODY, E.G. STENTS DIAGNOSIS ELECTRIC DIGITAL DATA PROCESSING FILTERS IMPLANTABLE INTO BLOOD VESSELS FIRST-AID KITS FOMENTATION HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA HUMAN NECESSITIES HYGIENE IDENTIFICATION INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS MEDICAL OR VETERINARY SCIENCE ORTHOPAEDIC, NURSING OR CONTRACEPTIVE DEVICES PHYSICS PROSTHESES SURGERY TREATMENT OR PROTECTION OF EYES OR EARS
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Beschreibung
Zusammenfassung:	The invention belongs to the field of cervical vertebra recovery, and particularly provides a cervical vertebra state recovery evaluation method and system based on deep learning, a temperature control cervical vertebra traction instrument applied to interactive communication and a user terminal, and the method comprises the steps: generating a cervical vertebra recovery evaluation request through the user terminal; the cervical vertebra recovery evaluation request is sent to a temperature control cervical vertebra traction instrument, and the real-time abnormal curvature of the cervical vertebra of the patient and cervical vertebra treatment data of the patient are collected; setting constraint conditions according to the real-time abnormal curvature and the body data of the patient, generating an optimal treatment curve determined based on a time scale, determining a target treatment function of the patient, and determining an ideal cervical traction track; and performing trajectory evaluation on the ideal