Quantification of head and trunk control for children with neuromotor and neuromuscular disorders

头部和躯干控制(躯干控制)对于日常功能活动的有效执行是强制性的，例如使用视觉、坐或任何上肢活动。患有脑性瘫痪(CP)、脊髓性肌萎缩症(SMA)和遗传性神经肌肉疾病(NMD)的儿童躯干控制功能受损，这是他们病情的基本组成部分。CP儿童躯干控制不良(定向头、坐平衡)与功能受损有直接关系，包括眼睛凝视交流、使用双手学习、游戏和社交发展、活动能力和尿失禁。脑性瘫痪程度较重的儿童从7岁开始功能减退。躯干控制的准确诊断可以使个性化的物理治疗在与常规治疗相结合的情况下，即使在严重的CP(预印本)中也能改善一般运动功能。需要一种准确、客观的工具来提供涵盖多种治疗方法和中心的证据。患有SMA1的婴儿与患有严重CP的儿童一样，在获得躯干控制方面存在类似的困难。使用Nusinesen，这些儿童现在可以存活下来，但这种药物很昂贵。需要一种准确、客观的测试来监测这种药物和替代药物的有效性。NMD儿童(SMA2、先天性肌病、先天性肌营养不良症、Duchenne肌营养不良症)日益严重的肌肉无力导致躯干控制能力的恶化和随后的脊柱侧弯。目的测量足够灵敏，以发现躯干控制的变化，脊柱侧弯前，将使适当的治疗，如在最佳时间进行物理治疗。我们的假设是，节段性躯干控制可以被客观有效地测量，分为七个节段性水平。这一客观测量将促进对躯干控制机制的新理解、监测治疗并为旨在改善姿势控制和相关运动功能的所有治疗策略的实践提供证据。目前所有适合在诊所使用的评估都是经过验证的，但依赖于临床判断，这种判断必须随着时间的推移而在治疗师之间保持，而且许多评估不能用于无法独自坐着的儿童。他们还将躯干视为一个单独的单元，从而失去了专业治疗所需的准确和详细的评估。我们预计这一客观的评估工具可以为全球成千上万的儿童，包括那些病情更严重的儿童，带来加强躯干控制的干预措施，从而提高功能技能。我们的项目将i)开发实时成像分析技术，以自动评估坐着时的躯干控制，ii)提供在任何诊所都可使用的成本效益和可获得的工具，而不增加评估时间，以及iii)发布在线互动数据库，传播用于测量躯干控制的公共标准、参考和培训资源，增进了解和增强专业知识。坐着时对儿童躯干控制的评估(400个CP、20个SMA1、40个典型发育期(TD)、40个NMD)将使用家庭市场提供的3D摄像机进行记录。该数据集将包括临床工具需要满足的所有躯干控制问题、身体形态和高度的示例。将使用机器学习方法来训练和验证自动诊断。该工具将根据专家临床评估进行验证，并作为笔记本电脑、软件和两个摄像头部署，适合临床工作人员在常规临床环境中使用。为了准备计划临床试验所需的功率计算，我们将收集20名CP儿童和5名SMA 1婴儿在12个月期间的纵向数据集。

Head and trunk control (trunk control) is mandatory for effective performance of everyday functional activities such as use of vision, sitting or any upper limb activity. Children with cerebral palsy (CP), spinal muscular atrophy (SMA) and inherited neuromuscular disorders (NMD) experience impairments in trunk control which are a fundamental component of their condition.Children with CP show a direct relationship between poor trunk control (orienting the head, sitting balance) and compromised function including communication by eye gaze, use of both hands for learning, play and social development, mobility and urinary incontinence. Children with more severe CP regress in their functional abilities from age 7 years. Accurate diagnosis of trunk control can enable individualised physiotherapy, when combined with treatment as usual, to improve general motor function even in severe CP (preprint). An accurate, objective tool is needed to provide evidence encompassing multiple therapies and centres.Infants with SMA1 have similar difficulty acquiring trunk control as do children with severe CP. Using Nusinersen, these children now survive, but this drug is expensive. An accurate, objective test is needed to monitor effectiveness of this and alternative drugs.The increasing muscle weakness in children with NMD (SMA2, congenital myopathy, congenital muscular dystrophy, Duchenne muscular dystrophy) leads to deterioration in trunk control with subsequent scoliosis. Objective measurement sensitive enough to detect changes in trunk control, pre-scoliosis, would enable appropriate treatment such as physiotherapy at the optimal time. Our hypothesis is that segmental trunk control can be measured objectively and efficiently, classified to seven segmental levels. This objective measurement would promote benefits in terms of new understanding of the mechanisms of trunk control, monitoring treatment and providing evidence to inform practice for all therapy strategies that aim to improve postural control and associated motor function. All current assessments suitable for use in a clinic are validated but rely on clinical judgement that must be maintained over time and between therapists, and many cannot be used for children unable to sit by themselves. They also consider the trunk as a single unit, thus losing the accurate and detailed assessment required for specialised therapy. We anticipate this objective assessment tool could lead to interventions to enhance trunk control, and thus improvement of functional skills, for thousands of children worldwide including those with greater severity of CP.Our project will i) develop live imaging analysis technology to automate the assessment of trunk control in sitting, ii) provide a cost effective and accessible tool usable within any clinic without increasing assessment time and iii) publish an online interactive database disseminating a public standard, a reference and a training resource for measuring trunk control, increasing understanding and enhancing expertise. Assessments of trunk control of children in sitting (400 CP, 20 SMA1, 40 typically developing (TD), 40 NMD) will be recorded using 3D cameras available for the home market. This dataset will include examples of all trunk control problems, body morphology and height that the clinical tool would be required to meet. Machine learning methods will be used to train and validate the automated diagnosis. The tool will be validated against expert clinical assessment and deployed as a laptop, software and two cameras, suitable for use by clinical staff in a routine clinical environment. To prepare power calculations necessary to plan clinical trials, we will collect a longitudinal dataset of 20 children with CP and 5 infants with SMA 1 during a twelve-month period.