Assessments are completely worthless unless they point directly to the 100% recovery protocols. I see nothing here that suggests you go from the assessment to the chosen 100% recovery protocol. When the hell will the stroke medical world do ANYTHING TO GET STROKE SOLVED? I'd have you all fired! A lot of dead wood needs to removed in stroke and until that occurs stroke will never be solved!
Validity of an android device for assessing mobility in people with chronic stroke and hemiparesis: a cross-sectional study
Journal of NeuroEngineering and Rehabilitation volume 21, Article number: 54 (2024)
Abstract
Background
Incorporating instrument measurements into clinical assessments can improve the accuracy of results when assessing mobility related to activities of daily living. This can assist clinicians in making evidence-based decisions. In this context, kinematic measures are considered essential for the assessment of sensorimotor recovery after stroke. The aim of this study was to assess the validity of using an Android device to evaluate kinematic data during the performance of a standardized mobility test in people with chronic stroke and hemiparesis.
Methods
This is a cross-sectional study including 36 individuals with chronic stroke and hemiparesis and 33 age-matched healthy subjects. A simple smartphone attached to the lumbar spine with an elastic band was used to measure participants’ kinematics during a standardized mobility test by using the inertial sensor embedded in it. This test includes postural control, walking, turning and sitting down, and standing up. Differences between stroke and non-stroke participants in the kinematic parameters obtained after data sensor processing were studied, as well as in the total execution and reaction times. Also, the relationship between the kinematic parameters and the community ambulation ability, degree of disability and functional mobility of individuals with stroke was studied.
Results
Compared to controls, participants with chronic stroke showed a larger medial-lateral displacement (p = 0.022) in bipedal stance, a higher medial-lateral range (p < 0.001) and a lower cranio-caudal range (p = 0.024) when walking, and lower turn-to-sit power (p = 0.001), turn-to-sit jerk (p = 0.026) and sit-to-stand jerk (p = 0.001) when assessing turn-to-sit-to-stand. Medial-lateral range and total execution time significantly correlated with all the clinical tests (p < 0.005), and resulted significantly different between independent and limited community ambulation patients (p = 0.042 and p = 0.006, respectively) as well as stroke participants with significant disability or slight/moderate disability (p = 0.024 and p = 0.041, respectively).
Conclusion
This study reports a valid, single, quick and easy-to-use test for assessing kinematic parameters in chronic stroke survivors by using a standardized mobility test with a smartphone. This measurement could provide valid clinical information on reaction time and kinematic parameters of postural control and gait, which can help(NOT GOOD ENOUGH! Come back when you have exact protocols for recovery!) in planning better intervention approaches.
Introduction
Stroke is the second-leading cause of death in adults and represents a major cause of disability worldwide [1]. There are 12.2 million new cases of stroke each year, and 101 million people are living with the consequences of a stroke [1]. This number has almost doubled in the last 30 years [1]. It is noteworthy that 70% of strokes and 87% of stroke-related deaths and disability-adjusted life-years occur in low- and middle-income countries [2]. The impact of persistent stroke-related disability is significant to both individuals and society. Therefore, there is an ongoing need to address the challenges faced by stroke survivors [3]. Stroke typically causes sensorimotor deficits such as muscle weakness in the paretic limbs, impaired proprioceptive capabilities, sensory loss, vision problems, and spasticity [4]. These deficits affect the postural stability of stroke survivors and have significant influence on their mobility [5], causing functional mobility impairment after stroke [6].
Since functionality is related to daily life activities (i.e., sitting and standing, walking, turning, and going up and down stairs) [6], its impairment negatively affects the quality of life of post-stroke subjects [7]. Furthermore, functional mobility in the community requires not only the ability to maintain balance while walking and turning, but also to ambulate at 0.80 m/s or faster [8, 9]. Thus, difficulties with mobility control, particularly in balance and gait, are a priority clinical concern in this population [10].
In that sense, monitoring the improvement of functional mobility post-stroke is relevant as it could help to determine the effect of rehabilitation and thus expand therapeutic options [11,12,13]. The gold standard measurement of functional mobility is photogrammetry [14]. However, it is time-consuming and difficult to perform in clinical practice. Therefore, several tests have been used in clinical settings and research to determine functional mobility in stroke. Particularly, the Time Up and Go Test (TUG) [7], the Tinetti’s Scale of Mobility and Balance [7], the Dynamic Gait Index [15] and the Rivermead Mobility Index [16, 17]. These tools are quick and easy to use and do not require expensive materials. However, they provide a subjective evaluation and are less sensitive in detecting changes [18]. Therefore, incorporating instrumental systems into clinical assessments could improve the accuracy of results. These devices provide objective information on biomechanical aspects such as posture, movement, and compensatory strategies [18].
In this regard, Lin et al. [5] compared the results of clinical assessment scales (lower extremity subscale of the Fugl-Meyer Assessment, Berg Balance Scale and TUG) versus instrumental balance assessment (stability, proprioception and limits of stability) and showed that the later was superior to clinical alternatives in detecting balance impairments in stroke patients with mild balance disorders. As a conclusion, these authors recommended that clinicians consider the use of both classic clinical tests and quantitative biomechanical tools when evaluating stroke patients to improve the accuracy of assessments, leading to a better individualized treatment plan [5]. Similarly, the Stroke Recovery and Rehabilitation Roundtable of the International Stroke Recovery and Rehabilitation Alliance considered kinematic measures to be essential in assessing sensorimotor recovery [19]. Therefore, the use of a device that can help measure kinematic data when performing several daily activity tasks (such as rising, walking, turning, and sitting down) in a single test could help clinicians in evidence-based decision making. For such a purpose, current evidence examines various technological approaches. Many of them are not portable or easy to move, and the evaluation procedure is complex and time-consuming [20]. As a result, researchers have begun using smartphone applications to assess walking activity and balance performance in stroke [21].
Smartphones are equipped with advanced computing capabilities, global positioning system receivers, and sensing capabilities such as an inertial measurement unit (IMU), magnetometer, and barometer [22]. These features can also be found in wearable ambulatory monitors [22]. Hence, smartphones are currently gaining interest in post-stroke clinical assessment due to their validity, reliability, portability and price [21, 23], not only for measuring upper limb range of motion [24] but particularly for gait and balance assessment [21]. A systematic review of smartphone technology [25] found that a few systems have utilized IMU sensors embedded in smartphones, while more systems have integrated external sensors for data acquisition and used the smartphone as a data processing unit in stroke patients. For gait and balance assessment, smartphones has primarily been used to determine step counts and cadence [26, 27], recognize human movement activity [28], study posturography [20, 29], and analyze kinematic data during gait [23, 30, 31]. It should be noted that the current scientific evidence indicates that more studies are needed [20, 21], especially with standardized protocols and appropriate sample calculations [21]. To the best of our knowledge, no study has been found that uses a smartphone in a single test to evaluate kinematic data during the joint performance of different tasks relevant to activities of daily living, such as reaction time, sitting down, getting up or turning around, in stroke population. Therefore, this study aimed to assess the validity of using an Android device to evaluate kinematic data during the execution of a standardized mobility test that includes various tasks relevant to activities of daily living in people with chronic stroke and hemiparesis. To achieve this objective, the data registered by the sensor were compared between stroke and non-stroke individuals. In addition, the relationship between clinical tests and kinematic parameters were studied for patients. If our working hypothesis is met, the inclusion of an inertial sensor on an Android device when performing a standardized mobility test will provide further information about which daily activity tasks have greater impairment in the population with chronic stroke, without the need to allocate more time for the clinical assessment.
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