Robotic assessment of the influence of age on upper-limb sensorimotor function

The differential effect of age on upper limb sensory processing, proprioception, and motor function

Sensory processing consists in the integration and interpretation of somatosensory information. It builds upon proprioception but is a distinct function requiring complex processing by the brain over time. Currently little is known about the effect of aging on sensory processing ability or the influence of other covariates such as motor function, proprioception, or cognition. In this study, we measured upper limb passive and active sensory processing, motor function, proprioception, and cognition in 40 healthy younger adults and 54 older adults. We analyzed age differences across all measures and evaluated the influence of covariates on sensory processing through regression. Our results showed larger effect sizes for age differences in sensory processing (r = 0.38) compared with motor function (r = 0.18-0.22) and proprioception (r = 0.10-0.27) but smaller than for cognition (r = 0.56-0.63). Aside from age, we found no evidence that sensory processing performance was related to motor function or proprioception, but active sensory processing was related to cognition (β = 0.30-0.42). In conclusion, sensory processing showed an age-related decline, whereas some proprioceptive and motor abilities were preserved across age.NEW & NOTEWORTHY Sensory processing consists in the integration and interpretation of sensory information by the brain over time and can be affected by lesion while proprioception remains intact. We investigated how sensory processing can be used to reproduce and identify shapes. We showed that the effect of age on sensory processing is more pronounced than its effect on proprioception or motor function. Age and cognition are related to sensory processing, not proprioception or motor function.

Change in the Results of Motor Coordination and Handgrip Strength Depending on Age and Body Position-An Observational Study of Stroke Patients and Healthy Volunteers

Objective: The stroke is considered a common disease of the elderly. Young people also get sick, but the risk of stroke increases with the age of 60. Stroke, regardless of the age of the patients, causes functional deficits; therefore, the aim of the study was to analyze the significance of the body position and examined upper limb on the parameters of motor coordination and handgrip strength in various age groups of people after stroke and healthy people. Material and method: This is an observational study. A total of 117 people participated in the study (60 stroke patients and 57 healthy people without neurological disorders). Both patients and healthy volunteers were prospectively divided into three age groups: 18−45, 46−60, and 61+. The tests were carried out in two starting positions: sitting without back support and lying on the back with the upper limb stabilized against the body. HandTutorTM and a hand dynamometer were used to assess the motor coordination, including the maximum range of motion and frequency of movement, as well as the grip strength. Results: The passive stabilization of the trunk and shoulder improved the maximum wrist ROM (p < 0.001) and frequency of finger movements (Hz F5 p = 0.018; F3 p = 0.010; F2 p = 0.011), especially in the oldest stroke patients. In the group of healthy volunteers, the most statistically significant results were obtained in the age range of 46−60. They occurred in both stable (wrist maxROM p = 0.041 and Hz F5 p = 0.034; Hz F4 p = 0.010; Hz F3 p = 0.028; Hz F1 p = 0.034, maxROM F1 p = 0.041) and unstable positions (maxROM F5 p = 0.034; maxROM F4 p = 0.050; maxROM F3 p = 0.002; maxROM F2 p = 0.002). In the group of the oldest healthy people, only one significant result was obtained in the stable position (Hz F3 p = 0.043). Conclusion: Passive stabilization of the trunk and examined upper limb improves the results of motor coordination of the distal part of the upper limb in both study groups. Passive stabilization of the trunk and upper limb improves motor coordination, especially in the oldest group of patients, after stroke.

A Comparative Analysis of 2D and 3D Tasks for Virtual Reality Therapies Based on Robotic-Assisted Neurorehabilitation for Post-stroke Patients

Post-stroke neurorehabilitation based on virtual therapies are performed completing repetitive exercises shown in visual electronic devices, whose content represents imaginary or daily life tasks. Currently, there are two ways of visualization of these task. 3D virtual environments are used to get a three dimensional space that represents the real world with a high level of detail, whose realism is determinated by the resolucion and fidelity of the objects of the task. Furthermore, 2D virtual environments are used to represent the tasks with a low degree of realism using techniques of bidimensional graphics. However, the type of visualization can influence the quality of perception of the task, affecting the patient's sensorimotor performance. The purpose of this paper was to evaluate if there were differences in patterns of kinematic movements when post-stroke patients performed a reach task viewing a virtual therapeutic game with two different type of visualization of virtual environment: 2D and 3D. Nine post-stroke patients have participated in the study receiving a virtual therapy assisted by PUPArm rehabilitation robot. Horizontal movements of the upper limb were performed to complete the aim of the tasks, which consist in reaching peripheral or perspective targets depending on the virtual environment shown. Various parameter types such as the maximum speed, reaction time, path length, or initial movement are analyzed from the data acquired objectively by the robotic device to evaluate the influence of the task visualization. At the end of the study, a usability survey was provided to each patient to analysis his/her satisfaction level. For all patients, the movement trajectories were enhanced when they completed the therapy. This fact suggests that patient's motor recovery was increased. Despite of the similarity in majority of the kinematic parameters, differences in reaction time and path length were higher using the 3D task. Regarding the success rates were very similar. In conclusion, the using of 2D environments in virtual therapy may be a more appropriate and comfortable way to perform tasks for upper limb rehabilitation of post-stroke patients, in terms of accuracy in order to effectuate optimal kinematic trajectories.