Yuta Furudate, Nanami Onuki, Kaori Chiba, Yuji Ishida, S. Mikami
{"title":"[常规论文]家庭康复中手指压力传感装置对手部运动功能恢复的自动评估","authors":"Yuta Furudate, Nanami Onuki, Kaori Chiba, Yuji Ishida, S. Mikami","doi":"10.1109/BIBE.2018.00047","DOIUrl":null,"url":null,"abstract":"Paralysis of fingers, which is caused by Hemiplegia, is difficult to recover. Patients often forced to leave hospital with paralysis remaining at hand. By this, a continuous rehabilitation at home is needed. However, it is difficult to carry out finger rehabilitation without help of therapists. To this end, we have been proposing an automated finger rehabilitation device which realizes home rehabilitation. A patient is asked by device to lift a finger, and the device measures whether undesirable movements are found on the other fingers by pressure sensors. To monitor an involuntary movement, it is necessary to evaluate the degree of the patient's condition of recovery. For this, we proposed a quantification method in our previous study. The method is based on the hypothesis that a patient is regarded as making recovery if his/her movement gets close to that of a healthy person. However, we consider only four fingers (index, middle, ring, little) are used to evaluate the degree of recovery because the thumb is different from the other finger in an anatomical structure. In this paper, we show a new recovery evaluation method that involves the sensor signals of all 5 fingers. We explain two possible evaluation methods: one is the model less simple integration method, and another is an integration by Generalized Linear Model (GLM). Comparing these methods, we conclude that the integration method by GLM provides a good scalar measurement of recovery, which was validated by the experiments conducted with patients who were previously evaluated by clinical scale.","PeriodicalId":127507,"journal":{"name":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"[Regular Paper] Automated Evaluation of Hand Motor Function Recovery by Using Finger Pressure Sensing Device for Home Rehabilitation\",\"authors\":\"Yuta Furudate, Nanami Onuki, Kaori Chiba, Yuji Ishida, S. Mikami\",\"doi\":\"10.1109/BIBE.2018.00047\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Paralysis of fingers, which is caused by Hemiplegia, is difficult to recover. Patients often forced to leave hospital with paralysis remaining at hand. By this, a continuous rehabilitation at home is needed. However, it is difficult to carry out finger rehabilitation without help of therapists. To this end, we have been proposing an automated finger rehabilitation device which realizes home rehabilitation. A patient is asked by device to lift a finger, and the device measures whether undesirable movements are found on the other fingers by pressure sensors. To monitor an involuntary movement, it is necessary to evaluate the degree of the patient's condition of recovery. For this, we proposed a quantification method in our previous study. The method is based on the hypothesis that a patient is regarded as making recovery if his/her movement gets close to that of a healthy person. However, we consider only four fingers (index, middle, ring, little) are used to evaluate the degree of recovery because the thumb is different from the other finger in an anatomical structure. In this paper, we show a new recovery evaluation method that involves the sensor signals of all 5 fingers. We explain two possible evaluation methods: one is the model less simple integration method, and another is an integration by Generalized Linear Model (GLM). Comparing these methods, we conclude that the integration method by GLM provides a good scalar measurement of recovery, which was validated by the experiments conducted with patients who were previously evaluated by clinical scale.\",\"PeriodicalId\":127507,\"journal\":{\"name\":\"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBE.2018.00047\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBE.2018.00047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
[Regular Paper] Automated Evaluation of Hand Motor Function Recovery by Using Finger Pressure Sensing Device for Home Rehabilitation
Paralysis of fingers, which is caused by Hemiplegia, is difficult to recover. Patients often forced to leave hospital with paralysis remaining at hand. By this, a continuous rehabilitation at home is needed. However, it is difficult to carry out finger rehabilitation without help of therapists. To this end, we have been proposing an automated finger rehabilitation device which realizes home rehabilitation. A patient is asked by device to lift a finger, and the device measures whether undesirable movements are found on the other fingers by pressure sensors. To monitor an involuntary movement, it is necessary to evaluate the degree of the patient's condition of recovery. For this, we proposed a quantification method in our previous study. The method is based on the hypothesis that a patient is regarded as making recovery if his/her movement gets close to that of a healthy person. However, we consider only four fingers (index, middle, ring, little) are used to evaluate the degree of recovery because the thumb is different from the other finger in an anatomical structure. In this paper, we show a new recovery evaluation method that involves the sensor signals of all 5 fingers. We explain two possible evaluation methods: one is the model less simple integration method, and another is an integration by Generalized Linear Model (GLM). Comparing these methods, we conclude that the integration method by GLM provides a good scalar measurement of recovery, which was validated by the experiments conducted with patients who were previously evaluated by clinical scale.