研究生: |
吳慧珉 Huey-Min Wu |
---|---|
論文名稱: |
視覺監控電腦化實作評量之效度化研究以感覺統合臨床觀察為例 The Sensory Integration Clinical Observation Using Visual Surveillance Based Computerized Performance Assessment and Its Validation |
指導教授: |
林世華
Lin, Sieh-Hwa |
學位類別: |
博士 Doctor |
系所名稱: |
教育心理與輔導學系 Department of Educational Psychology and Counseling |
論文出版年: | 2009 |
畢業學年度: | 97 |
語文別: | 中文 |
論文頁數: | 137 |
中文關鍵詞: | 視覺監控 、感覺統合臨床觀察 、感覺統合功能障礙 、實作評量 、樣式辨識 |
英文關鍵詞: | pattern recognition, performance assessments, sensory integration clinical observation, sensory integration dysfunction, visual surveillance |
論文種類: | 學術論文 |
相關次數: | 點閱:250 下載:26 |
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本研究是以「感覺統合臨床觀察」為主要研究領域,從實作評量之觀點,探討使用視覺監控分析人物目標之姿勢動作並結合樣式辨識,應用於診斷受試者感覺統合障礙之有效性。
研究結論彙整如下:
一、本研究根據感覺統合臨床觀察電腦計分模式所發展的感覺統合臨床觀察電腦化診斷工具,具有良好之信度與效度,適用於診斷感覺統合臨床觀察之障礙類別。
二、「趴姿伸直」與「臥姿彎曲」之重要觀測向度(頭部、胸部、手部、腳部、協同性、穩定度)診斷,最大概似分類器之診斷正確率最高。
三、原始資料型態在「趴姿伸直」與「臥姿彎曲」各重要觀測向度之訊息融合時,具有較高之診斷正確率。
四、在「趴姿伸直」整體診斷時,選取頭部、手部、腳部之向度在最大概似分類器可以提升診斷正確率;在「臥姿彎曲」整體診斷時,選取頭部、手部、協同性、穩定度之向度在最大概似分類器可以提升診斷正確率。
五、年齡層不同之受試者在「趴姿伸直」與「臥姿彎曲」之量的表現(持久度)有顯著差異, 5歲的受試者優於4歲的受試者。
六、在4歲年齡層,不同性別之受試者在「趴姿伸直」之量的表現有顯著差異,女生在「趴姿伸直」之量的表現優於男生;在5歲~6歲之年齡層,性別之不同在「趴姿伸直」與「臥姿彎曲」之量的表現有顯著差異,女生均優於男生。
七、不同性別受試者在「趴姿伸直」與「臥姿彎曲」之質的表現有顯著性差異,男生感覺統合功能障礙的人數在「趴姿伸直」與「臥姿彎曲」皆多於女生。
Abstract
The purpose of this study is to develop a computerized assessment tool for sensory integration clinical observation. Based on the view of performance assessments, the pattern recognition is combined with the visual surveillance procedures to analyze the posture movements (prone extension and supine flexion) and to diagnose the sensory integration dysfunction of subjects in this study.
The major findings of this study are summarized as follows:
1. With good properties in both reliability and validity, the computerized assessment tool for sensory integration clinical observation developed in this study has good performances in diagnosing disorder of sensory integration functions of subjects.
2. The prediction rates for employing the maximum likelihood classifier are best in diagnosing disorder of sensory integration functions in terms of important features of prone extension and supine flexion.
3. The prediction rates for raw data information are best in diagnosing deficits of sensory integration functions in terms of prone extension and supine flexion.
4. Selecting the features of head, hands, and feet can improve the prediction rates in the maximum likelihood classifier in terms of prone extension; selecting the features of head, hands, coordination, and stability can improve the prediction rates in the maximum likelihood classifier in terms of supine flexion.
5. Analysis of variance (ANOVA) indicates that there were statistically significances on year groups in terms of quantity performances of prone extension and supine flexion. The performance of the 5-year olds subjects is better than the 4-year olds subjects.
6. From the 4-year olds to the 6-year olds , ANOVA indicates that there were statistically significances on gender groups in terms of quantity performances of prone extension and supine flexion. The performance of girls is better than boys.
7. Chi-square testing indicates that there were statistically significances on gender groups in terms of quality performances of prone extension and supine flexion. The number of boys with sensory integration dysfunction is much more than girls.
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