شناسايي اختلال راه رفتن افراد مبتلا به ناتواني حركتي مفصل زانو با استفاده از سيستم فازي

Recognition of gait disorder in people with knee joint disability using FUZZY system

اﺧﺘﻼل در راه رﻓﺘﻦ ﯾﮏ ﻣﺸﮑﻞ ﺷﺎﯾﻊ در ﺟﺎﻣﻌﻪ اﺳﺖ ﮐﻪ ﻣﯽ ﺗﻮاﻧﺪ ﺑﻪ ﻋﻨﻮان ﯾﮏ آﺳﯿﺐ، زﻧﺪﮔﯽ ﻓﺮد را ﻣﺤﺪود ﮐﻨﺪ. ﺗﺸﺨﯿﺺ ﺻﺤﯿﺢ و ﺳﺮﯾﻊ اﯾﻦ اﺧﺘﻼل ﻣﯽ ﺗﻮاﻧﺪ ﺑﻪ روﻧﺪ ﺑﻬﺒﻮد و درﻣﺎن ﮐﻤﮏ ﮐﻨﺪ، ازاﯾﻦ رو ﻫﻤﻮاره ﭘﮋوﻫﺶ ﻫﺎﯾﯽ اﻧﺠﺎم ﺷﺪه اﺳﺖ ﮐﻪ ﺑﺮ ﻣﺒﻨﺎي آن ﭘﺰﺷﮏ ﺑﺘﻮاﻧﺪ ﯾﮏ ﺑﺮﻧﺎﻣﻪ درﻣﺎﻧﯽ ﻣﻨﺎﺳﺐ ﺑﺮاي ﺑﯿﻤﺎر در ﻧﻈﺮ ﺑﮕﯿﺮد. در اﯾﻦ ﭘﮋوﻫﺶ از ﯾﮏ ﺣﺴﮕﺮ ﮐﯿﻨﮑﺖ ﮐﻪ ﻗﺎﺑﻠﯿﺖ ﺷﻨﺎﺳﺎﯾﯽ 25 ﻧﻘﻄﻪ از ﻧﻘﺎط آﻧﺎﺗﻮﻣﯿﮑﯽ ﺑﺪن ﻓﺮد را دارد ﺑﻪ ﻣﻨﻈﻮر درﯾﺎﻓﺖ و ﺛﺒﺖ داده اﺳﺘﻔﺎده ﺷﺪه اﺳﺖ، ﺑﺮ ﻣﺒﻨﺎي اﻃﻼﻋﺎت ﺳﻪ ﺑﻌﺪي ﺑﻪ دﺳﺖ آﻣﺪه از 25 ﻧﻘﻄﻪ، ﺗﻌﺪاد 8 وﯾﮋﮔﯽ اﺳﺘﺨﺮاج ﺷﺪ ﮐﻪ ﻧﺘﺎﯾﺞ ﻧﺸﺎن داده اﺳﺖ ﺗﻌﺪاد 7 وﯾﮋﮔﯽ اﺳﺘﺨﺮاج ﺷﺪه، ﺗﻔﮑﯿﮏ ﭘﺬﯾﺮي ﺑﻬﺘﺮي داﺷﺘﻨﺪ. راﻫﮑﺎر ﻣﻮردﻧﻈﺮ ﺑﺮ ﻣﺒﻨﺎي ﺳﯿﺴﺘﻢ ﻓﺎزي ﺗﻌﺮﯾﻒ ﺷﺪه ﮐﻪ ﯾﮏ ﮔﺮوه ﭘﺰﺷﮑﯽ ﺑﻪ ﻋﻨﻮان ﺧﺒﺮه در اﯾﻦ ﺳﯿﺴﺘﻢ ﻫﻤﮑﺎري ﻣﯽ ﻧﻤﺎﯾﻨﺪ. ﺗﻌﺪاد ﺷﺮﮐﺖ ﮐﻨﻨﺪﮔﺎن 90 ﻧﻔﺮ ﻣﯽ ﺑﺎﺷﺪ ﮐﻪ در ﮔﺎم اول از ﻣﺠﻤﻮع داده ﻫﺎي 50 ﻧﻔﺮ ﺑﯿﻤﺎر ﺣﺮﮐﺘﯽ و 40 ﻧﻔﺮ اﻓﺮاد ﺳﺎﻟﻢ، از داده ي 45 ﻧﻔﺮ ﺑﺮاي اﺳﺘﺨﺮاج ﻗﻮاﻋﺪ ﻓﺎزي ﺑﺮ ﻣﺒﻨﺎي ﻧﻈﺮات ﺧﺒﺮﮔﺎن اﺳﺘﻔﺎده ﺷﺪ ﻫﻤﭽﻨﯿﻦ ﺑﺮاي اﯾﻨﮑﻪ در ﺳﺎﺧﺖ ﻣﺪل ﺑﺎﯾﺎس ﮐﻤﺘﺮي اﺗﻔﺎق ﺑﯿﻮﻓﺘﺪ از روش k-fold در دﺳﺘﻪ ﺑﻨﺪي داده ﻫﺎ اﺳﺘﻔﺎده ﺷﺪه اﺳﺖ.در ﮔﺎم دوم از داده ي 45 ﻧﻔﺮ دﯾﮕﺮ ﺑﺮاي ارزﯾﺎﺑﯽ ﺳﯿﺴﺘﻢ ﭘﯿﺸﻨﻬﺎدي اﺳﺘﻔﺎده ﮔﺮدﯾﺪ. ﺧﺮوﺟﯽ ﻫﺎي ﺣﺎﺻﻞ از ﺻﺤﺖ ﺳﻨﺠﯽ ﺳﯿﺴﺘﻢ ﻓﺎزي ﻧﺸﺎن ﻣﯽ دﻫﺪ ﮐﻪ ﺑﺮ ﻣﺒﻨﺎي 7 وﯾﮋﮔﯽ ﺗﻌﺮﯾﻒ ﺷﺪه و ﻗﻮاﻋﺪ ﺳﺎﺧﺘﻪ در ﺳﯿﺴﺘﻢ ﻓﺎزي، دﻗﺖ، ﮔﺰارش ﺷﺪه 95 درﺻﺪ اﺳﺖ.

Gait disorder is an issue in human society that can limit a person's life activity as an injury. Correct and rapid diagnosis of this disorder can help the healing process. Therefore, research has always been done to identify this disorder, based on which the physician can consider an appropriate treatment plan for the patient. Many recent studies have used different wearable and non-wearable sensors for identification. In the present study, Kinect sensor, which can identify 25 points of anatomical points of a person's body, was used to receive and record data, the identification method is defined based on the Fuzzy System defined by a medical team consisting of specialists and knee surgeons as experts in this system. The number of participants is 90, which is given from the data of 45 people in the training step and construction of the fuzzy system based on the opinions of experts, and in the second step from the data of another 45 people to evaluate the system as input. The outputs of the fuzzy system validation show that based on 7 defined features and rules made in the fuzzy system, the accuracy, precision, and recall are reported are 95%, 92.14%, and 89.26%, respectively.