在台灣，隨著人口結構老化，高齡者的照護需求成為急需因應的問題，而跌倒不僅是高齡者主要的事故傷害之一，伴隨的照護人力、資源的花費更是可觀。因此，本研究以預防跌倒為目的，分析中高齡與高齡族群在不同情境下執行足部定位任務時所採取的腳眼協調策略，並與表現績效連結；後續依照參與者所採取的腳眼協調策略的動作、視線特徵，提供可行之改善建議，期能提昇參與者之績效表現，以降低在居家環境跌倒之風險、減輕社會負擔。
本研究招募40位參與者，其中20位為55歲以上之中高齡與高齡族群（男性10人、女性10人；平均年齡：64.3歲），另有20位為20至30歲之年輕族群（男性10人、女性10人；平均年齡：23.3歲）做為對照組，藉以觀察身體機能較佳者所採取之腳眼協調策略。參與者裸視或矯正後視力需達0.5以上，並以「柏格氏平衡量表（Berg Balance Scale, BBS）總分41分以上、計時起身行走（Timed Up & Go Test, TUG）完成時間在12秒以內」做為行動能力篩選基準，藉此減少年齡以外之個人差異造成的影響。
為探討腳眼協調策略對任務績效指標的影響，以及討論個人因素、環境因素對腳眼協調策略影響，實驗為三因子混合設計，第一個因子─個人因素（年齡族群）─為參與者間因子，有兩種等級（中高齡與高齡族群、年輕族群），其餘兩個因子─環境因素（障礙物高度、障礙物擺放距離）─為參與者內因子，其中，障礙物高度包含三種障礙物高度（0公分、5公分、10公分），障礙物擺放距離則包含兩種障礙物在踩踏目標前之距離（一步距、兩步距），因此，總共有六種不同複雜度的任務。每次試驗中，參與者都必須從起點位置出發往前走，在跨越踩踏目標前的障礙物後，將雙腳踩在終點上的指定目標內，並以足部定位精準度、任務完成時間為主任務績效指標。此外，走道前方2公尺的螢幕會在每次試驗中皆會於參與者踩踏目標之前導腳腳趾離地、抬至最高點時依序顯示兩種不同顏色（紅、橙、黃、綠、藍、紫等六色中隨機挑選兩種，但互不為互補色、鄰近色），參與者在雙腳定位後即回答所看到螢幕中之顏色，以評估視覺次任務之績效（有無答對顏色）。實驗中以紅外線動作擷取系統蒐集參與者之下肢動作，輔以穿戴式眼球軌跡追蹤儀記錄參與者之視線行為。
在資料的預處理上，將每位參與者踩踏目標前四步中的每一步週期標準化並切為10等分，以每步的第0、10、20、…、100百分比（percent）做為關鍵影格（key frame），總計41個關鍵影格；並蒐集每個關鍵影格中的頸椎、脊椎、雙腳髖關節、膝關節與踝關節的屈曲/伸展（flexion/extension）角度以及眼球垂直方向轉動角度等共9項變數。
接著利用主成分分析（Principal Component Analysis, PCA）擷取11個累積解釋變異量達71.7%之主成分（Principal Component, PC），並定義為11種不同的腳眼協調特徵，再根據主成分分數（PC score），利用集群分析（cluster analysis）將樣本分群並定義出四種腳眼協調策略：策略1「彎腰踩踏目標」、策略2「踩踏目標時抬高下肢」、策略3「在踩踏目標前一步抬高下肢、再平穩踩踏」、策略4「視線向前」。隨後使用混合線性模型（linear mixed model）探討腳眼協調特徵對主任務績效指標（足部定位精準度、任務完成時間）的影響，另利用羅吉斯迴歸（logistic regression）檢定腳眼協調特徵與視覺次任務（有無答對顏色）的關聯性。
結果顯示：多數腳眼協調特徵對主任務或次任務的績效表現有顯著影響。在不同腳眼協調特徵中，有關視線角度的腳眼協調特徵與參與者的任務表現較相關，即適當的視線轉移有助於提高足部定位精準度或顏色回答正確率。此外，因參與者之注意力資源有限，需在不同績效（踩踏誤差、任務完成時間、有無答對顏色）之間進行注意力分配的取捨，並無任何腳眼協調特徵可反映兼顧較佳之主任務與次任務績效。再探討個人因素（年齡族群）、環境因素（障礙物擺放位置、高度）對腳眼協調特徵之影響，發現中高齡與高齡族群之腳眼協調特徵與年輕族群不同，在以前導腳踩踏目標的前期，中高齡與高齡族群身體前彎之角度較年輕族群大；另環境因素亦對腳眼協調特徵有顯著影響，參與者普遍會依障礙物之擺放位置、高度調整下肢抬舉的高度。最後探討腳眼協調策略對績效指標的影響，結果顯示策略4（視線向前）之足部定位精準度最差，且此策略多為中高齡與高齡族群所採取，會在以跟隨腳踩踏目標前期將視線從目標上提早轉移到前方螢幕上。根據文獻，建議採取策略4之參與者在腳跟接觸目標後再將視線轉離，以提昇足部定位精準度。

Falls are one of the most important issues among middle-aged and elderly populations. It is hence needed to develop early interventions for reducing their falling risk. Therefore, this study aims to help prevent falls among middle-aged and elderly people by analyzing their foot-eye coordination strategies while performing foot positioning tasks under different conditions.
40 participants were recruited in this study, including 20 middle-aged and elderly people above 55 years old (10 males and 10 females; mean age= 64.3 years) and 20 young adults in the range of 20 to 30 years old (10 males and 10 females; mean age= 23.3 years). All participants had 20/40 vision or better, achieved a score higher than 41 on Berg Balance Scale (BBS), completed Timed Up & Go Test (TUG) in no more than 12 seconds, and self-reported no known musculoskeletal or neurological impairments.
The experiment was a three-way mixed model design. One factor was between-subject (individual difference: age), while the other two were within-subject (environmental factors: obstacle height and position). There were 2 levels of age (young, elderly), 3 levels of obstacle height (0cm, 5cm, 10cm), and 2 levels (1step, 2steps) of the distance between the obstacle and the target. Hence, there is a total of six different conditions. Each participant was asked to walk from the starting position and step over the obstacle while positioning both feet onto specified targets. The positioning error and completion time were defined as the performance measure of the primary task. Besides, two different colors were displayed from leading foot’s toe-off to mid-swing and from mid-swing to heel-strike of the leading foot respectively. The participant had to recall the colors being seen as the performance measure of secondary task. Each participant was required to wear the eye-tracking glasses and motion capture suit, for collecting gaze behavior and motion data.
The last four steps before the participants’ both feet stepping on the target were considered. Each step was divided into 10 time-equivalent segments. Thus, 40 segments with 41 key frames were generated for each trial. There are 9 parameters obtained, including the flexion/extension angles of neck, spine, hips, knees, and ankles, as well as the vertical gaze angle.
Principal component analysis (PCA) was first conducted with the gait and gaze data collected. 11 Principal components (PCs) accounted in total of 71.7% of variance were extracted. Cluster analysis was then used to determine four different strategies based on the PC scores, including bending the trunk (strategy 1), lifting the leg high while stepping on target (strategy 2), lifting the leg high as one-step before stepping on target (strategy 3), walking and looking ahead (strategy 4). Linear mixed model was then performed to test if foot-eye coordinations affect the performance of the primary task (foot positioning and completion time), while logistic regression was performed to find out if different coordinations result in different performance of the secondary task (percentage of correct responses).
It was found that the foot-eye coordinations which were related to gaze behavior had higher correlations with the performance of the tasks. In other words, a proper gaze transfer would contribute to better foot positioning or higher percentage of correct responses of the secondary task. Also, trade-offs between the primary and the secondary tasks in visual attention were found. Therefore, there was no specific strategy contributing to better performance for both primary and secondary tasks. Besides, strategy 4 had the worst performance of foot positioning task, and this strategy was adopted more by middle-aged and elderly people. It showed that the participants who adopted strategy 4 had earlier gaze transfer to the monitor for displaying secondary task, leading to the larger foot positioning errors. Based on the literature review, it is suggested that participants who took strategy 4 should not transfer gaze until heel-contact on the target to enhance the foot positioning accuracy and reduce the falling risk.

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