足下垂患者康复保健关键技术研究与实现
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摘要
随着经济的高速发展和老龄化社会的到来,人们越来越关注自身和家人的保健与康复,对保健康复类服务和技术的需求日益增长。由于脑卒中(脑中风)引起足下垂患者的数量十分庞大,这些患者的生活质量因足下垂病症而受到较大的影响。如何使足下垂患者通过使用辅具适应日常生活并得到康复是目前研究的焦点之一；由于足下垂患者在日常生活中极容易发生跌倒,如何及时准确检测患者的跌倒和对跌倒进行有效预警是非常重要的保健措施,也是研究的重点之一；足下垂患者需要通过一定的运动锻炼进行康复,伴随家庭运动健身器材的增多,居家无氧运动健身已成为一种时尚,如何评估无氧运动对心血管系统的影响也是研究的热点之一
本文针对脑中风引起的足下垂患者康复和保健中的足下垂自适应刺激康复、跌倒检测和预警以及运动康复三方面的科学和技术问题进行研究与相应的技术设备实现,主要结果和结论如下：
(1)针对目前由脑中风引起的足下垂刺激康复技术存在的刺激周期不易与患者行走节奏同步、不能区分患者的日常生活状态、且需要手动开启和关闭刺激信号的发放等问题,本文依据现代信号检测、识别与处理技术,提出了一种足下垂自适应刺激辅助行走与康复技术,并采用双轴倾角传感器和单片机技术进行了完整的系统设计与实现。该技术与系统采用双轴倾角传感器获取人体的姿态信息,采用平滑滤波技术对获取的原始数据进行噪声抑制,引入短时傅里叶变换和小波变换寻找刺激的最佳时刻,达到与患者行走姿态自适应匹配的目的。该技术与系统通过BP神经网对胫骨倾角分类的方法识别患者的行走状态与非行走状态,从而对系统发放的刺激信号脉冲进行自适应开启与关闭的控制。另一方面,该技术与系统能够通过对足下垂患者的自适应刺激,在辅助行走的同时起到一定的康复作用。实验表明,本文提出的足下垂自适应刺激康复系统的刺激时刻正确率在正常行走时超过97.5%,在上楼梯时超过95.8%,在下楼梯时接近99%,具有很好的患者状态自适应功能。
(2)针对足下垂患者易于发生跌倒,而目前对人体跌倒的检测方法不能实现跌倒预警的现状,本文在研究人体解剖结构的基础上,提出了一种基于人体状态检测识别的跌倒检测与预警新方法,并采用双轴倾角传感器和单片机技术进行了系统的设计与实现。该方法采用双轴倾角传感器监测人体的姿态(状态)信息,利用BP神经网络对人体多种日常与跌倒状态进行粗分类,初步区分跌倒与非跌倒,对于易于与跌倒混淆的弯腰等动作,采用三段数据分析法进行进一步的分析确认,依据数学形态学、倾角变化率和跌倒与倾角关系函数等信号处理手段寻找确认监测信号中倾向于跌倒的特征和可能的跌倒方向,在跌倒发生前及时报警或采取保护措施。实验表明,上述跌倒监测与预警方法可以使96.21%的跌倒在即将发生时得到正确检测,为减小跌倒造成的伤害提供了有效的预警时间,对于足下垂患者和其他老年人的保护具有重要的意义。
(3)针对足下垂患者运动康复与保健问题中存在的疑问和误区,本文以功率自行车运动为例系统研究了无氧下肢运动对颈总动脉血液动力学特性所产生的影响,试图对足下垂患者及其他人群的运动康复与保健提供有益的指导与参考。本文以不同性别的年轻健康被试作为研究对象,使用功率自行车持续进行四组强度相同的无氧下肢运动训练。用彩色超声多普勒检测系统分别检测被试在静息状态和每组运动训练后的颈总动脉管径与轴心流速波形,同时记录血压和心率。依据经典血液动力学理论对检测数据进行分析,计算颈总动脉的弹性模量和局部血液动力学参数。实验与分析结果表明,上述无氧下肢运动后,被试心率增加,且随着运动的累积,颈总动脉弹性模量呈增加趋势；一个心动周期内轴心血流速度和流量率最大值与平均值上升,流速和流量率最小值下降；收缩压和平均压增高,舒张压无明显改变；周向应变无明显改变；切应力最大值有明显增加趋势,切应力最小值下降趋势明显；振荡剪切指数也有增大趋势。上述血液动力学特性变化表明：无氧下肢运动训练可能降低颈总动脉的弹性功能,并对颈总动脉血液动力学产生负面影响。本文研究不仅为足下垂患者的康复运动选择提供指导,对其他人群的运动锻炼也提供了有益的参考。
本文的研究结果和结论,不仅有助于进一步开发足下垂自适应刺激康复系统和跌倒检测与预警系统,同时也为正确利用无氧功率自行车开展运动保健、康复工作提供了有价值的血液动力学信息。
As the rapid development of economy and the arrival of the aging society, people pay more and more attentions to themselves as well as their family's healthcare and rehabilitation, thus the demands of the health rehabilitation service and products are growing fast. A huge number of patients who are effected by footdrop are suffering low quality lives because of stroke. Thus, how to help them via all kinds of facilities to adapt their daily lives and get recovered has become one of our main interests. Since the footdroppers are always so easy to fall and hurt themselves, how to detect the falls timely and accurately, and also how to inform the related with prewarnings have become a second one of our main focuse. With the increase in family sports fitness equipment, anaerobic exercise home fitness has become a fad. The footdrop patients also need some exercises to get recovered, so a third one of our hot points is how to evaluate the effects of aerobic exercise on cardiovascular system.
In order to solve the problems above, this thesis mainly discusses, as well as, realizes three issues of adaptive stimulation of footdrop, the detecting and prewarning of the elderly falls and exercise rehabilitation. The main results and discussions are as follows:
(1) Since it's always difficult to realize the synchronization between stimulations and the movement of footdrop patients who experienced stroke, and it's also hard to distinguish their normal from disable which makes it a must that the patients manually switch stimulation signal. In order to solve these problems, this paper puts forward a new technology for both adaptive stimulation of footdrop and rehabilation based on morden signal detecting, analyzing and processing, and we are believed to be the first to use the dual-axis inclinometer sensor and MCU to design and realize the whole system. We introduce biaxial inclination sensors for posture, the mean filter and Savitzky-Golay filter for raw data denosing and STFT, wavelet algorithm for optimum moments to send simulation signals. On one hand, BP artificial neural network is put forward to distinguish walking from non-walking using tibial angle information and it helps us when to when to send adaptive stimulation and control signals automatically, and on the other, this techonoly and the new system can do both stimulation and rehabilation just like two birds with one stone. By virtue of the adaptive simulation system, one can obtain97.5%accuracy of walking,95.8%accuracy of up the stairs and almost99%accuracy of down the stairs.
(2) Since footdrop patients often fall down and get hurt and methods to make prewarnings of falling are still no where to be found, we put forward a new method and a new system which realizes fall detecting and prewarning based on research in anthropomorphology and study in anatomy by dual-axis inclinometer sensor and MCU. Experimentally realize the biaxial inclination sensor detection system to monitor body postures and introduce BP neural network to distinguish normal state from falling state roughly. Moreover, further analysis is made to determine more puzzle postures, e.g. bending over and falling, using three-stage data method. Furthermore, warnings and protection in advance are made based on mathematical morphology and signal processing method such as the function of angle rate which help to identify falling tendency and possible falling direction. Through this method, more than96.21%of the falling can be early warned, providing the effective early warning time to reduce falling damage; Actually distinguish the action in the daily life hence reducing the fall detection errors and improving the practicability of the detection.
(3) Since there have always been questions and misunderstandings in healthcare and habilation for footdrop patients, systematically research in the effection of hemodynamic function parameters of common carotid artery controlled by anaerobic power bicycle exercises is carried out in order to provide useful guidance for the rehabilation for the rehabilitation, general health and exercise of patients with foot drop, we take young healthy volunteers with different genders as the research object, we use the anaerobic power bicycle to do four sets of the accurate exercise training at the same strength. Color doppler ultrasound imaging detection system were used to detect the resting state, the axis velocity waveform and carotid artery diameter waveform after each set of exercise training. Detect heart rate and blood pressure value via electronic automatic blood pressure meter. Calculate the elastic modulus of the common carotid artery and local hemodynamic parameters, including pressure-strain elastic modulus, flow rate, circumferential strain, wall shear stress and oscillatory shear index through the classical theory of hemodynamic analysis of test data. The results showed that the heart rate increases after the exercise; carotid artery elastic modulus tended to increase with the accumulation of movement; maximum and average value of the axial flow velocity and flow rate in one cardiac cycle are increasing whilst, the minimum value of flow rate decrease; systolic blood pressure and mean pressure increase anddiastolic blood pressure did not change significantly; circumferential strain did not change significantly; the maximum shear stress increases and the minimum value of shear stress decreases obviously; oscillatory shear index is also having an increasing trend. These results suggest that anaerobic power cycling may reduce the elastic function of the carotid artery, meanwhile have a negative impact on the common carotid artery hemodynamics that is different with the aerobic exercise's enhancement on the arterial elasticity. This study provide useful adviceabout rebilitation exercises and sports training for both the footdrop patients and other groups.
These studies not only contribute to the further development of the elderly fall detection and warning system and rehabilitation system of footdrop adaptive stimulation, but also provide some useful hemodynamic information in order to correctly use anaerobic power bicycle sport for healthcare and rehabilitation.
本文针对脑中风引起的足下垂患者康复和保健中的足下垂自适应刺激康复、跌倒检测和预警以及运动康复三方面的科学和技术问题进行研究与相应的技术设备实现,主要结果和结论如下：
(1)针对目前由脑中风引起的足下垂刺激康复技术存在的刺激周期不易与患者行走节奏同步、不能区分患者的日常生活状态、且需要手动开启和关闭刺激信号的发放等问题,本文依据现代信号检测、识别与处理技术,提出了一种足下垂自适应刺激辅助行走与康复技术,并采用双轴倾角传感器和单片机技术进行了完整的系统设计与实现。该技术与系统采用双轴倾角传感器获取人体的姿态信息,采用平滑滤波技术对获取的原始数据进行噪声抑制,引入短时傅里叶变换和小波变换寻找刺激的最佳时刻,达到与患者行走姿态自适应匹配的目的。该技术与系统通过BP神经网对胫骨倾角分类的方法识别患者的行走状态与非行走状态,从而对系统发放的刺激信号脉冲进行自适应开启与关闭的控制。另一方面,该技术与系统能够通过对足下垂患者的自适应刺激,在辅助行走的同时起到一定的康复作用。实验表明,本文提出的足下垂自适应刺激康复系统的刺激时刻正确率在正常行走时超过97.5%,在上楼梯时超过95.8%,在下楼梯时接近99%,具有很好的患者状态自适应功能。
(2)针对足下垂患者易于发生跌倒,而目前对人体跌倒的检测方法不能实现跌倒预警的现状,本文在研究人体解剖结构的基础上,提出了一种基于人体状态检测识别的跌倒检测与预警新方法,并采用双轴倾角传感器和单片机技术进行了系统的设计与实现。该方法采用双轴倾角传感器监测人体的姿态(状态)信息,利用BP神经网络对人体多种日常与跌倒状态进行粗分类,初步区分跌倒与非跌倒,对于易于与跌倒混淆的弯腰等动作,采用三段数据分析法进行进一步的分析确认,依据数学形态学、倾角变化率和跌倒与倾角关系函数等信号处理手段寻找确认监测信号中倾向于跌倒的特征和可能的跌倒方向,在跌倒发生前及时报警或采取保护措施。实验表明,上述跌倒监测与预警方法可以使96.21%的跌倒在即将发生时得到正确检测,为减小跌倒造成的伤害提供了有效的预警时间,对于足下垂患者和其他老年人的保护具有重要的意义。
(3)针对足下垂患者运动康复与保健问题中存在的疑问和误区,本文以功率自行车运动为例系统研究了无氧下肢运动对颈总动脉血液动力学特性所产生的影响,试图对足下垂患者及其他人群的运动康复与保健提供有益的指导与参考。本文以不同性别的年轻健康被试作为研究对象,使用功率自行车持续进行四组强度相同的无氧下肢运动训练。用彩色超声多普勒检测系统分别检测被试在静息状态和每组运动训练后的颈总动脉管径与轴心流速波形,同时记录血压和心率。依据经典血液动力学理论对检测数据进行分析,计算颈总动脉的弹性模量和局部血液动力学参数。实验与分析结果表明,上述无氧下肢运动后,被试心率增加,且随着运动的累积,颈总动脉弹性模量呈增加趋势；一个心动周期内轴心血流速度和流量率最大值与平均值上升,流速和流量率最小值下降；收缩压和平均压增高,舒张压无明显改变；周向应变无明显改变；切应力最大值有明显增加趋势,切应力最小值下降趋势明显；振荡剪切指数也有增大趋势。上述血液动力学特性变化表明：无氧下肢运动训练可能降低颈总动脉的弹性功能,并对颈总动脉血液动力学产生负面影响。本文研究不仅为足下垂患者的康复运动选择提供指导,对其他人群的运动锻炼也提供了有益的参考。
本文的研究结果和结论,不仅有助于进一步开发足下垂自适应刺激康复系统和跌倒检测与预警系统,同时也为正确利用无氧功率自行车开展运动保健、康复工作提供了有价值的血液动力学信息。
As the rapid development of economy and the arrival of the aging society, people pay more and more attentions to themselves as well as their family's healthcare and rehabilitation, thus the demands of the health rehabilitation service and products are growing fast. A huge number of patients who are effected by footdrop are suffering low quality lives because of stroke. Thus, how to help them via all kinds of facilities to adapt their daily lives and get recovered has become one of our main interests. Since the footdroppers are always so easy to fall and hurt themselves, how to detect the falls timely and accurately, and also how to inform the related with prewarnings have become a second one of our main focuse. With the increase in family sports fitness equipment, anaerobic exercise home fitness has become a fad. The footdrop patients also need some exercises to get recovered, so a third one of our hot points is how to evaluate the effects of aerobic exercise on cardiovascular system.
In order to solve the problems above, this thesis mainly discusses, as well as, realizes three issues of adaptive stimulation of footdrop, the detecting and prewarning of the elderly falls and exercise rehabilitation. The main results and discussions are as follows:
(1) Since it's always difficult to realize the synchronization between stimulations and the movement of footdrop patients who experienced stroke, and it's also hard to distinguish their normal from disable which makes it a must that the patients manually switch stimulation signal. In order to solve these problems, this paper puts forward a new technology for both adaptive stimulation of footdrop and rehabilation based on morden signal detecting, analyzing and processing, and we are believed to be the first to use the dual-axis inclinometer sensor and MCU to design and realize the whole system. We introduce biaxial inclination sensors for posture, the mean filter and Savitzky-Golay filter for raw data denosing and STFT, wavelet algorithm for optimum moments to send simulation signals. On one hand, BP artificial neural network is put forward to distinguish walking from non-walking using tibial angle information and it helps us when to when to send adaptive stimulation and control signals automatically, and on the other, this techonoly and the new system can do both stimulation and rehabilation just like two birds with one stone. By virtue of the adaptive simulation system, one can obtain97.5%accuracy of walking,95.8%accuracy of up the stairs and almost99%accuracy of down the stairs.
(2) Since footdrop patients often fall down and get hurt and methods to make prewarnings of falling are still no where to be found, we put forward a new method and a new system which realizes fall detecting and prewarning based on research in anthropomorphology and study in anatomy by dual-axis inclinometer sensor and MCU. Experimentally realize the biaxial inclination sensor detection system to monitor body postures and introduce BP neural network to distinguish normal state from falling state roughly. Moreover, further analysis is made to determine more puzzle postures, e.g. bending over and falling, using three-stage data method. Furthermore, warnings and protection in advance are made based on mathematical morphology and signal processing method such as the function of angle rate which help to identify falling tendency and possible falling direction. Through this method, more than96.21%of the falling can be early warned, providing the effective early warning time to reduce falling damage; Actually distinguish the action in the daily life hence reducing the fall detection errors and improving the practicability of the detection.
(3) Since there have always been questions and misunderstandings in healthcare and habilation for footdrop patients, systematically research in the effection of hemodynamic function parameters of common carotid artery controlled by anaerobic power bicycle exercises is carried out in order to provide useful guidance for the rehabilation for the rehabilitation, general health and exercise of patients with foot drop, we take young healthy volunteers with different genders as the research object, we use the anaerobic power bicycle to do four sets of the accurate exercise training at the same strength. Color doppler ultrasound imaging detection system were used to detect the resting state, the axis velocity waveform and carotid artery diameter waveform after each set of exercise training. Detect heart rate and blood pressure value via electronic automatic blood pressure meter. Calculate the elastic modulus of the common carotid artery and local hemodynamic parameters, including pressure-strain elastic modulus, flow rate, circumferential strain, wall shear stress and oscillatory shear index through the classical theory of hemodynamic analysis of test data. The results showed that the heart rate increases after the exercise; carotid artery elastic modulus tended to increase with the accumulation of movement; maximum and average value of the axial flow velocity and flow rate in one cardiac cycle are increasing whilst, the minimum value of flow rate decrease; systolic blood pressure and mean pressure increase anddiastolic blood pressure did not change significantly; circumferential strain did not change significantly; the maximum shear stress increases and the minimum value of shear stress decreases obviously; oscillatory shear index is also having an increasing trend. These results suggest that anaerobic power cycling may reduce the elastic function of the carotid artery, meanwhile have a negative impact on the common carotid artery hemodynamics that is different with the aerobic exercise's enhancement on the arterial elasticity. This study provide useful adviceabout rebilitation exercises and sports training for both the footdrop patients and other groups.
These studies not only contribute to the further development of the elderly fall detection and warning system and rehabilitation system of footdrop adaptive stimulation, but also provide some useful hemodynamic information in order to correctly use anaerobic power bicycle sport for healthcare and rehabilitation.
引文
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