著者

圓尾 知之 中江 文 前田 倫 高橋−成田 香代子 Morris Shayn 横江 勝 松崎 大河 柴田 政彦 齋藤 洋一

出版者

日本疼痛学会

雑誌

PAIN RESEARCH (ISSN:09158588)

巻号頁・発行日

vol.28, no.1, pp.43-53, 2013-03-10 (Released:2013-04-04)

参考文献数

15

被引用文献数

1 12

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Background: The revised version of Short-Form McGill Pain Questionnaire (SF-MPQ-2) has been developed as a tool for measuring both neuropathic and non-neuropathic pain which can be used in studies of epidemiology, pathophysiologic mechanisms, and treatment response. SF-MPQ-2 was expanded and revised from the Short-Form McGill Pain Questionnaire (SF-MPQ-1) pain descriptors by adding symptoms relevant to neuropathic pain and by modifying the response format to a 0 - 10 numerical rating scale. In this study, we translated the SF-MPQ-2 into Japanese. The aim of this study was the validation of a Japanese version of the SF-MPQ-2 in patients with neuropathic pain. Materials and Methods: A total of 110 chronic pain patients from Osaka University Hospital and Nishinomiya Municipal Central Hospital were enrolled in this study, with 87 (47 males, 40 females) patients completing the study. Enrolled patients completed the SF-MPQ-2 which had been translated into Japanese. To evaluate the validity of the SF-MPQ-2 questionnaire, an exploratory factor analysis was performed. For assessment of reliability, we used internal consistency reliability coefficients (Cronbach's alpha coefficient) and the test-retest method test (Intraclass Correlation Coefficient; ICC) for the SF-MPQ-2 total and subscale scores. Validity was evaluated by examining the associations between the SF-MPQ-2 total and subscale scores and other measures. Results: The internal consistency (Cronbach's alpha coefficient; continuous pain; α=0.883, intermittent pain; α=0.856, predominantly neuropathic pain; α=0.905, affective descriptors; α=0.863, total score; α=0.906) and reproducibility coefficient (ICC; continuous pain; ρ=0.793, intermittent pain; ρ=0.750, predominantly neuropathic pain; ρ=0.819, affective descriptors; ρ=0.760, total score; ρ=0.830) were high. There were significant correlations between SF-MPQ-2 and other functional assessments. Conclusion: Our findings showed excellent reliability and validity for the Japanese version of the SF-MPQ-2 in pain patients, and the results of both exploratory and confirmatory factor analyses provided support for four readily interpretable subscales (continuous pain, intermittent pain, pre-dominantly neuropathic pain, and affective descriptors). These results provide a basis for use of the SF-MPQ-2 in future clinical research, including clinical trials of treatments for neuropathic and non-neuropathic pain conditions.

著者

加藤 拓哉 関野 正樹 松崎 大河 西川 敦 齋藤 洋一 大崎 博之

出版者

公益社団法人 日本生体医工学会

雑誌

生体医工学 (ISSN:1347443X)

巻号頁・発行日

vol.50, no.1, pp.180-188, 2012-02-10 (Released:2012-07-13)

参考文献数

21

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We previously proposed an eccentric figure-eight coil design which induces sufficient currents in the brain at lower output powers of stimulator. In the present study, numerical analyses were performed with various coil design parameters, such as outer and inner diameters and number of turns, to investigate the influence of these parameters on the eddy current distribution in the brain and the coil characteristics. Increases in the inner diameter, the outer diameter, and the number of turns caused increases in the induced currents. In order to downsize the stimulator system, we need to strengthen the eddy current in the brain, maintaining inductance as small as possible. Our results show that it is effective to enlarge outer diameter. In addition, there is only small difference in the eddy current distributions between the eccentric coil and the concentric coil in direction along with the coil plane and with depth of the brain.

著者

福島 大志 西川 敦 宮崎 文夫 関野 正樹 安室 喜弘 松崎 大河 細見 晃一 齋藤 洋一

出版者

公益社団法人 日本生体医工学会

雑誌

生体医工学 (ISSN:1347443X)

巻号頁・発行日

vol.49, no.1, pp.122-131, 2011-02-10 (Released:2011-12-13)

参考文献数

16

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Repetitive Transcranial Magnetic Stimulation (rTMS) is effective for intractable diseases of the nervous system. As the effects of rTMS last only several hours, rTMS therapies need to be continued daily. Under present circumstances, it is difficult to use rTMS in patients' home, because only experienced physicians in limited hospitals can use the expensive and complicated rTMS system. Therefore, we developed a magnetic navigation system for home use of rTMS. The proposed system uses inexpensive and small magnetic sensors; hence it is suitable for home use. By using the proposed method, even people who have no medical knowledge and technique can easily navigate the coil to the optimal position preliminarily specified by expert physicians. Our system needs to collect some dataset which consists of magnetic field and the corresponding position of the coil at the patients' initial visit. Since it is bothersome to collect a large number of dataset, we reduced the dataset by approximation using multi-regression analysis.

著者

福島 大志 西川 敦 宮崎 文夫 関野 正樹 安室 喜弘 松崎 大河 細見 晃一 齋藤 洋一

出版者

Japanese Society for Medical and Biological Engineering

雑誌

生体医工学 (ISSN:1347443X)

巻号頁・発行日

vol.49, no.1, pp.122-131, 2011

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Repetitive Transcranial Magnetic Stimulation (rTMS) is effective for intractable diseases of the nervous system. As the effects of rTMS last only several hours, rTMS therapies need to be continued daily. Under present circumstances, it is difficult to use rTMS in patients' home, because only experienced physicians in limited hospitals can use the expensive and complicated rTMS system. Therefore, we developed a magnetic navigation system for home use of rTMS. The proposed system uses inexpensive and small magnetic sensors; hence it is suitable for home use. By using the proposed method, even people who have no medical knowledge and technique can easily navigate the coil to the optimal position preliminarily specified by expert physicians. Our system needs to collect some dataset which consists of magnetic field and the corresponding position of the coil at the patients' initial visit. Since it is bothersome to collect a large number of dataset, we reduced the dataset by approximation using multi-regression analysis.