從中風中恢復是一個複雜的過程，而其中一個最具挑戰性的部分就是重新獲得行走的能力。中風倖存者經常因平衡障礙而導致步態不對稱，這會妨礙他們自信且安全地行走。但如果我們能夠精確測量這些步態差異，來更好地理解潛在問題，並提供更具針對性的復健呢？最近，隨著運動分析和數據科學的進步，這一目標正變得可能。

一篇發表在2024 Scientific Report的文章，由Jieun C. 等人發表(連結)，使用主成分分析 (Principle Componet Analysis, PCA) 來識別中風倖存者在行走時的關鍵步態模式。這種方法將複雜的運動數據分解為幾個成分，使我們能夠清楚地看到受影響的（癱瘓）和未受影響的（健側）肢體在行走週期中的行為。通過了解這些差異，我們可以幫助中風患者更有效地康復，並提高他們的生活質量。

中風倖存者步態不對稱的重要性
步態不對稱，即步行模式不均勻，是中風倖存者的典型特徵。研究顯示，高達 55.5% 的中風患者會經歷步態不對稱，這會引發一系列問題：

平衡控制減弱
增加能量消耗
增加跌倒風險
肌肉骨骼疼痛
這些問題源於癱瘓和健側肢體之間的平衡失調，兩側在行走時難以協調。傳統的復健通常只關注癱瘓側，但最新研究顯示，健側肢體在步態中的作用同樣關鍵。通過同時考慮兩側，我們可以更全面地了解中風倖存者的步態。

使用 PCA 揭示步態模式
主成分分析 (PCA) 在分析中風患者的步態方面表現出色。在一項最新研究中，研究人員利用 PCA 評估中風患者的關節運動，結果顯示了有平衡障礙患者（低BBS組）與平衡較好患者（高BBS組）之間的顯著差異。研究結果表明：

癱瘓肢體：步行擺動階段中踝關節和膝關節的變異性增大。
健側肢體：踝關節背屈增加，膝關節變異性增大。
兩側關節的變異性均增加，進而加重平衡障礙，影響整體步態穩定性。
這些結果強調了中風對身體兩側的不同影響，而任何有效的復健策略都應考慮這一點。通過 PCA，臨床醫生可以精確找出步態中平衡受損的階段，並針對性地調整干預措施。

關注的關鍵步態參數
一些可以表明中風相關障礙的重要步態參數包括：

步長：有平衡障礙的患者通常顯示出較短的步長，特別是在癱瘓側。
擺動時間與支撐時間：每隻腳的擺動（離地）和支撐（著地）時間的不均衡能夠揭示步態不對稱。
雙支撐時間：雙腳同時著地的時間長短可以顯示患者為維持平衡而採取的補償策略。
關節變異性：尤其是在矢狀面（前後方向）和水平面的關節角度變異性是平衡缺陷的標誌。

步態復健的未來
隨著AI動作偵測技術和 PCA 的發展，我們正邁向更加個性化的復健計畫。不再僅依賴通用的訓練，臨床醫生可以根據數據得出的洞察，針對每位患者的具體問題進行干預。通過同時處理癱瘓側和健側肢體，復健計畫能夠改善平衡、步行速度和整體行走能力。

對於中風存活者來說，這種方法帶來了更快、更有效康復的希望。步態分析提供了一種清晰的方式來衡量康復進展，讓患者和臨床醫生可以即時看到治療效果。隨著技術的進一步發展，我們將有望看到更精確的工具來評估和改善中風後的移動能力。

結論
使用 PCA 進行中風復健分析揭示了步態和平衡障礙的複雜性。通過同時分析身體兩側，我們能夠更好地理解如何解決中風倖存者面臨的獨特挑戰。這種基於數據的方式提供了一條通向更有效治療的道路，使患者能夠重新獲得獨立性並改善生活質量。

如果您或您的親友正在進行中風復健，請考慮探索步態分析的好處。透過正確的工具和洞察，康復不僅是可能的，而且是可衡量的。

以下是英文版
Unlocking the Secrets of Stroke Recovery: How Gait Analysis Can Help Quantify Balance Impairments

Recovering from a stroke is a complex journey, and one of the most challenging aspects is regaining mobility. Stroke survivors often experience asymmetry in their gait due to balance impairments, which can hinder their ability to walk confidently and safely. But what if we could precisely measure those gait differences to better understand the underlying issues and provide more targeted rehabilitation? Recent advancements in motion analysis and data science are making this possible.

One promising approach involves using Principal Component Analysis (PCA) to identify key patterns in the way stroke survivors walk. This method breaks down complex movement data into components, allowing us to see exactly how the affected (paretic) and unaffected (nonparetic) limbs behave during the walking cycle. By understanding these differences, we can help stroke patients recover more efficiently and improve their quality of life.

The Importance of Gait Asymmetry in Stroke Survivors

Asymmetric gait, or uneven walking patterns, is a hallmark of stroke survivors. Studies show that up to 55.5% of stroke patients experience this asymmetry, which can lead to a range of challenges:

• Reduced balance control
• Increased energy expenditure
• Higher risk of falls
• Musculoskeletal pain

These problems arise from the imbalance between the paretic and nonparetic limbs, which struggle to work together during walking. Traditional rehabilitation often focuses solely on the affected side, but emerging research suggests that the nonparetic limb plays a critical role too. By looking at both sides of the body, we can better understand the full picture of a stroke survivor’s gait.

Using PCA to Uncover Gait Patterns

Principal Component Analysis (PCA) has proven to be a game-changer in analyzing stroke gait. In a recent study, researchers used PCA to evaluate the joint movements of stroke patients as they walked. The analysis revealed key differences between patients with balance impairments (Berg Balance Scale low group) and those with better balance control (BBS high group). The results showed:

• Increased variability in the paretic limb, especially in the ankle and knee joints during the swing phase of walking.
• Significant differences in the nonparetic limb, with greater ankle dorsiflexion and knee variability.
• Higher joint variability in both limbs, contributing to balance impairments and affecting overall gait stability.

These findings emphasize that stroke affects both sides of the body in unique ways, and any effective rehabilitation strategy should take this into account. By using PCA, clinicians can pinpoint the exact phases of gait where balance is compromised and tailor interventions accordingly.

Key Gait Parameters to Watch

Some of the most important gait parameters that can indicate stroke-related impairments include:

• Step Length: Patients with balance impairments typically show reduced step length, particularly on the paretic side.
• Swing and Stance Time: Imbalances in how long each foot is in the air (swing) or on the ground (stance) provide insight into asymmetry.
• Double Support Time: The amount of time both feet are on the ground can indicate compensatory strategies to maintain balance.
• Joint Variability: Increased variability in joint angles, particularly in the sagittal (front-to-back) and horizontal planes, is a marker of balance deficits.

The Future of Gait Rehabilitation

With advancements in motion capture and PCA, we’re moving towards more personalized rehabilitation plans. Instead of relying on generic exercises, clinicians can now use data-driven insights to target specific issues in each patient’s gait. By addressing both the paretic and nonparetic limbs, rehabilitation programs can improve balance, walking speed, and overall mobility.

For stroke survivors, this approach brings hope for a quicker and more effective recovery. Gait analysis offers a clear way to measure progress, allowing patients and clinicians to see the results of therapy in real-time. As technology continues to evolve, we’ll likely see even more precise tools for assessing and improving mobility after stroke.

Conclusion

The use of PCA in stroke rehabilitation is unlocking new insights into the complexities of gait and balance. By analyzing both sides of the body, we can better understand how to address the unique challenges faced by stroke survivors. This data-driven approach offers a path to more effective treatments, allowing patients to regain their independence and improve their quality of life.

If you or someone you know is undergoing stroke rehabilitation, consider exploring the benefits of gait analysis. With the right tools and insights, recovery is not only possible but measurable.