Real-Time 4D Facial Sensing and Modelling

慢性面瘫是由贝尔氏麻痹和中风等疾病引起的，保守估计，英国每年新增51640人。根据英国对Bell‘s面瘫患者和需要专家治疗的残留虚弱患者的发病率数据进行的估计(约30%)表明，每年治疗所有新患者的费用可能在2,543,000 GB(单独治疗)到7,948,000 GB(治疗加肉毒毒素注射)之间。大约30%的面瘫患者持续遭受慢性毁容、焦虑和/或抑郁。事实证明，为这些患者提供的服务是有限的。面瘫的治疗费用很高。随着NHS要求每年节省数十亿美元(NHS，2011)，重新考虑传统的治疗途径势在必行。NHS国家中风物理治疗临床指南建议面瘫患者每天接受45分钟的面部治疗。为了满足指南，每个患者将需要至少12周的每日面对面治疗(广义上定义为急性期)，每个患者的费用为NHS GB 2400。由于每年有26,000个新病例，这意味着除了治疗现有患者的费用外，这些新患者每年的费用将高达62,400,000 GB。然而，可以通过开发一种基于家庭的康复技术来降低成本，使更多的患者能够接受黄金标准的治疗。所提出的技术将为患者在家中接受治疗时提供实时反馈，从而显著减少拜访治疗师进行面对面反馈的时间。本项目将研究4D(动态三维)技术和集成镜像视觉反馈MVF理论的计算模型，用于使用深度传感器进行家庭治疗。该框架设想开发易于使用的面瘫治疗技术，该技术可以结合MVF理论提供实时反馈评估患者的治疗反应。使用MVF疗法治疗幻肢疼痛和复杂区域疼痛综合征的研究取得了令人振奋的结果。如果锻炼面部肌肉，面瘫患者可以更快地恢复。然而，由于焦虑地看着自己不对称和畸形的面部特征，患者面对镜子可能会很痛苦。因此，我们将应用MVF自适应地镜像面部的健康侧和不健康侧的面部运动，从而允许患者在锻炼面部肌肉时观察健康的整个面部。有报道称，基于MVF的生物反馈疗法对Bell面瘫和三叉神经痛的半面性疼痛具有较好的疗效。然而，这些研究要么使用物理镜框，要么使用简单的基于图像的映射，提供的反馈很少或面部运动信息不准确。患者对面部表现出的异常动作的意识有限，因此如果没有对这些动作的反馈，他们的面部功能可能会恶化，出现永久性的异常动作。因此，迫切需要新的计算4D传感和建模方法来开发能够根据MVF捕捉和绘制准确的面部肌肉运动的治疗方法。最终目标是将这种方法编程到一个软件包中，用于家庭治疗。目前，还没有基于MVF的3D或4D产品或技术可用于治疗。因此，所提出的用于建立集成MVF的计算4D传感和建模模型的方法将通过在评估患者的治疗反应时提供适当的反馈而极大地有利于患者和NHS，并最终提高扩展基于家庭的治疗的能力。它还可以用于远程康复的实际应用，因此临床顾问和治疗师可以远程观察患者的家庭治疗。

Chronic Facial Palsy is caused by conditions including Bell's palsy and Stroke, afflicting, at a conservative estimate, 51,640 new people per year in the UK. Estimates based on UK incidence data for Bell's palsy patients and those left with residual weakness requiring specialist management (approximately 30%) suggests that to treat all new patients could cost between £2,543,000 (therapy alone) to £7,948,000 (therapy plus botulinum toxin injections) per annum. Approximately 30% of patients affected by facial palsy suffer ongoing chronic disfigurement, anxiety and/or depression. It has been shown that service provision for these patients is limited. Facial palsy management is expensive. With the NHS requiring to save billions annually (NHS, 2011), it is imperative to rethink conventional treatment pathways. The NHS National Clinical Guidelines for Stroke physiotherapy recommends 45 minutes daily facial therapy for patients with facial paralysis. To meet the guidelines, each patient would need daily face-to-face therapy for a period of at least 12 weeks (broadly defined as the acute phase), costing the NHS £2,400 per patient. With 26,000 new cases annually this would represent a prohibitive cost of £62,400,000 for these new patients per annum on top of the cost of treating existing patients. However, costs could be reduced by developing a home-based rehabilitative technology, allowing greater numbers of patients to receive gold-standard treatment. The proposed technologies will provide patients with real-time feedback when undergoing therapy at home and thus can significantly reduce the time of visiting therapists for face-to-face feedback.This project will investigate 4D (dynamic three-dimension) techniques and a computational model integrating Mirror Visual Feedback MVF theory for home-based therapy using a depth sensor. This framework envisions developing easy to use facial palsy therapy technologies, which can provide real-time feedback assessing treatment responses of patients integrating MVF theory. Research studies using MVF therapy to treat phantom limb pain and complex regional pain syndrome have produced promising results. Facial palsy patients can recover more quickly if they exercise their facial muscles. However, it can be painful for patients to face mirrors due to the anxiety of looking at their asymmetric and deformed facial features. Therefore, we will apply MVF to adaptively mirror the healthy side of the face and facial movement over the unhealthy side and thus allow patients to observe healthy whole faces when exercising their facial muscles. It has been reported that biofeedback therapy based on MVF has been effective for Bell's facial palsy and hemi-facial pain of trigeminal neuralgia. However, these studies either use a physical mirror box or simple image-based mapping, which provide little feedback or inaccurate facial movement information. Patients have limited awareness of the abnormal movements their faces display so without feedback about these movements their facial functions may worsen, developing permanently abnormal movements. Therefore, there is a strong need for novel computational 4D sensing and modelling methods to develop therapy which can capture and map accurate facial muscle movements according to MVF. The ultimate goal is to programme this method into a software package for home-based therapy. Currently, there are no 3D or 4D products or technologies based on MVF available for therapy. Thus, the proposed methods for building computational 4D sensing and modelling models integrating MVF will be hugely beneficial to patients and the NHS by providing appropriate feedback in assessing treatment responses of patients and ultimately improve the ability to scale home-based therapy. It can also be adapted to tele-rehabilitation for practical applications so clinical consultants and therapists can remotely observe patients' home-based therapy.