DetectFoG : Detection of Gait Freezing Episodes in Parkinsonian Patients Using Inertial
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 20
- 试验地点
- 2
- 主要终点
- Precision
研究概览
简要总结
Parkinson's disease is the second most common neurodegenerative disease in the world. One of these manifestations is the freezing of gait (FOG) which affects 50 to 80% of Parkinsonian patients. It is defined as a brief and episodic absence or marked reduction in the forward progression of the feet despite the intention to walk. FOG is one of the most disabling symptoms causing a greater risk of falling and a loss of autonomy for these patients. This symptom is little or not dopamine-sensitive and little improved by surgery (deep brain stimulation).
Although this symptom is common and debilitating, it is difficult to assess clinically. The objective assessment of the presence and severity of FOG episodes can be done with tests such as the New-Freezing of Gait Questionnaire (N-FOGQ) with however limitations. Indeed, this filmed examination is scored a posteriori and the accumulation of the administration times which makes it difficult to use in routine clinical practice. To overcome these limitations, the use of a diary completed by the patient himself is a simple alternative to assess this symptom, but studies show that patients abandon this practice in the long term and that it is not used by patients with cognitive impairment.
Recent advances in miniaturization have made it possible to create light and compact sensors to assess these events objectively. Inertial measurement units have been widely used in the literature to detect FOG episodes. The choice of the detection algorithms are a major issue in the scientific community. To date, due to the heterogeneity of the protocols, no method is currently required as a reference.
The objective is to evaluate the accuracy of a new algorithm to detect the number of FOG episodes in Parkinsonian patients. This evaluation will be done on the freeze-inducing walking path.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Sequential
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patient over 18 years old
- •With Parkinson's disease according to the United Kingdom Brain Bank criteria
- •Presenting episodes of freezing of gait assessed on the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS II - question 13 with a score between 1 and 3 in order to have a patient walking without technical assistance) produced by the neurologist
- •Able to walk 30 meters independently
- •Affiliated to a social security scheme or beneficiary of such a scheme
- •Having signed a free and informed consent in writing
排除标准
- •Montreal Cognitive Assessment (MOCA) < 20/30
- •Other neurological or orthopedic history that interferes with walking
- •Pregnant, parturient or breastfeeding women
- •Adults subject to legal protection (safeguard of justice, curatorship, guardianship), persons deprived of liberty
- •Persons undergoing psychiatric care, persons admitted to a health or social establishment for purposes other than research
- •Persons unable to express their consent
- •Simultaneous participation in another research related to balance and/or walking
结局指标
主要结局
Precision
时间窗: Through study completion, an average of 15+/-7 days
Every second of the course will be analyzed to define : * the "true positive" time: FOG detected by the algorithm and the two experts * True negative" time: FOG detected by neither the algorithm nor the two experts * False positive" time: FOG detected by the algorithm but not by the two experts * False negative" time: FOG not detected by the algorithm but detected by both experts For each course completed, accuracy will then be calculated as the ratio between the sum of the time spent in "true positive" and "true negative" divided by the time taken to complete the course. The average of these ratios is then calculated to estimate the accuracy of all runs performed, i.e. taking into account all repetitions performed by patients, regardless of run type and ON/OFF status.
次要结局
- Sensitivity(Through study completion, an average of 15+/-7 days)
- Specificity(Through study completion, an average of 15+/-7 days)
- Positive predictive value (PPV)(Through study completion, an average of 15+/-7 days)
- Negative predictive value (NPV)(Through study completion, an average of 15+/-7 days)
- Time difference(Through study completion, an average of 15+/-7 days)