Abstract
With the popularization of rehabilitation robots, it is necessary to develop quantitative motor function assessment methods for patients with a stroke. To make the assessment equipment easier to use in clinics and combine the assessment methods with the rehabilitation training process, this paper proposes an anthropomorphic rehabilitation robot based on the basic movement patterns of the upper limb, point-to-point reaching and circle drawing movement. This paper analyzes patients’ movement characteristics in aspects of movement range, movement accuracy, and movement smoothness and the output force characteristics by involving 8 patients. Besides, a quantitative assessment method is also proposed based on multivariate fitting methods. It can be concluded that the area of the real trajectory and movement accuracy during circle drawing movement as well as the ratio of force along the sagittal axis in backward point-to-point movement are the unique parameters that are different remarkably between stroke patients and healthy subjects. The fitting function has a high goodness of fit with the Fugl-Meyer scores for the upper limb (, ), which demonstrates that the fitting function can be used to assess patients’ upper limb movement function. The indicators are recorded during training movement, and the fitting function can calculate the scores immediately, which makes the functional assessment quantitative and timely. Combining the training process and assessment, the quantitative assessment method will farther expand the application of rehabilitation robots.
1. Introduction
Stroke is one common disease caused by abnormal blood supply, about 15% hemorrhagic and 85% ischemic blood [1]. Almost 85% of patients with a stroke have difficulties with their hemiplegic upper limb during daily life [2]. Once a stroke patient has been in steady state after drug therapy, he/she will receive many rehabilitation trainings to promote recovery and prevent complications [3]. To be clear about the motor function state of patients and make customized training schedules for patients, therapies should make function assessment.
In the early stage, researchers focused on muscle strength assessment [4]. With the increasing cases of stroke patients, therapists and researchers had developed many function assessment scales such as Brunnstrom Scales and Fugl-Meyer Scales [5–7]. However, with rehabilitation training methods changed by intelligent equipment such as rehabilitation robots, the assessment methods are needed to be improved. Scales’ assessment methods are dependent on therapists’ experience. To make the assessment methods impersonal and combined with intelligent equipment, it is necessary to develop quantitative methods for motor function assessment.
Many researchers have made studies on quantitative assessment methods. Ellis et al. [8] and Murphy et al. [9] analyzed the range of the joint angle and movement during point-to-point reaching movement by an optoelectronic three-dimensional motion capture system and pointed out that the absolute range of movement was usually influenced by individual difference. Fasoli et al. [10] proposed that the movement time and peak velocity can be used to analyze the effect of instructions on functional performance for patients. Murphy et al. [11] and Wagner et al. [12] analyzed the average velocity, the maximum velocity, and peak velocity during the drinking daily activity and found the maximum velocity was different between different stages of patients. What is more, researchers analyzed the movement accuracy by the movement direction deviation, the movement straightness [13], and ellipticity [14], which was found to have remarkable relevance with the impairment degree for stroke patients. Researchers also analyzed the movement smoothness by calculating the number of peak velocity, but there was some inconsistency in the relationship between it and patients’ recovery stages. In 2006, Kahn et al. [13] found the increased number reflexed improvement during rehabilitation programs for chronic patients. However, Colombo et al. [15] and Panerese et al. [16] found the number reduced during patients’ improvement.
Although many researches have been made on the quantitative assessment, inconsistency still exists in the relationship between the parameters and the motor function, which may be caused by the different movement patterns in the researches. Some researchers analyzed the fetching for the glass movement in daily life [13, 17–19], and some researchers analyzed the circle drawing movement in the desired trajectory [14, 15]. It is important to analyze the principal movement patterns for patients’ motor function assessment. Besides, most of the quantitative assessment methods relied on the complicated optoelectronic three-dimensional motion capture system, which may be difficult to use in clinics [20–22]. It is also important to make quantitative assessment equipment easier to establish for clinical use.
Intending to make the movement patterns during function assessment standard and make the quantitative assessment equipment easier to use, this paper analyzes the principal movement patterns and proposes an anthropomorphic rehabilitation robot based on the principal movement patterns. Besides, this paper analyzes the patients’ movement characteristics in aspects of movement range, movement accuracy, movement smoothness, and output force characteristics during the principal movement patterns. It also proposes the quantitative functional assessment method based on the parameters, which were remarkably correlated with functional assessment scores. This proposed assessment method based on the rehabilitation robot combines the assessment process with the rehabilitation training process, which will further the automation of rehabilitation robots and the application of rehabilitation robots in clinics.
2. Materials and Methods
2.1. The Movement Patterns of Upper Limb for Motor Function Assessment
The point-to-point reaching movement was considered the basic movement pattern of the upper limb that made up most of the daily behavior [23]. The point-to-point reaching movement primarily involved shoulder flexion/extension and elbow flexion/extension. In order to assess more coordinate movements between shoulder and elbow joints, the circle drawing movement was added as the second basic movement pattern, which involved more ranges of shoulder internal/external rotation and shoulder abduction/adduction as well as shoulder flexion/extension and elbow flexion/extension [14].
To demonstrate the circle drawing movement involved more coordinate movement between shoulder and elbow joints, nine healthy people were involved to act the required movement patterns. Every person was required to perform a point-to-point reaching movement and a circle drawing movement, whose diameter was the range of point-to-point reaching movement in a plane, shown in Figure 1(a).
(a)
(b)
(c)
Figure 1
The movement patterns of upper limb and the structure of end-effector upper limb rehabilitation robot for assessment (EEULRbot): (a) the movement patterns of upper limb, (b) the structure of EEULRbot with human model, and (c) the definition of angles of shoulder and elbow joints.
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TBI Rehabilitation 