The daily activities of individuals with stroke are significantly influenced by the upper limb (UL) and hand function. ¹ Evidence from several studies suggested that 85% of stroke survivors suffer UL and hand impairments. ^{2 – 5} In particular stroke survivors with middle cerebral artery infarction have been associated with muscle weakness, ⁶ inability to control all UL segments in space and time (inter-joint coordination), ^{7 , 8} difficulty in grasping and holding an object, and reduced ability to independently move individual fingers. ³ There is significant evidence to suggest that these UL impairments contribute to loss of UL function, loss of independence in activities of daily living, and impaired quality of life. ^{9 , 10} The presence of these diverse motor impairments a few weeks after a stroke can predict future UL function. ³ Therefore, evaluation of UL function is critical in day-to-day stroke rehabilitation. ¹¹

Evaluation of UL functional movements following stroke has been performed by several types of tools ranging from observer-based scales, instrumented tests, and self-reported questionnaires. ¹² Some of the commonly reported reliable and valid performance assessment tools to quantify UL function in stroke survivors include the Fugl-Meyer Assessment of Upper Limb (FMA-UL), Wolf Motor Function Test (WMFT), Action Research Arm Test (ARAT), Box and Block Test (BBT), Nine Hole Peg Test (NHPT). ^{12 – 14} Although FMA-UL has been reported to have the highest level of psychometric and clinometric properties, it does not evaluate functional arm and hand movements. ¹⁵ FMA-UL mainly evaluates body function and structures as per the international classification of functioning (ICF) framework. In addition, FMA-UL and ARAT are noted to exhibit some overlap in their assessment of UL function, suggesting that they may not be entirely distinct in their evaluations of UL capabilities. ¹⁶ Clinical tools such as ARAT, WMFT, BBT, and NHPT predominantly measure grasping and displacement movements of different object sizes with less emphasis on gross movements. ^{17 , 18} ARAT involves a subjective scoring method, with poor definitions of the test item positioning and time allocation for each item. ^{14 , 19} Currently, there is no agreement on the selection of any particular tool for a particular individual with a stroke. ³

Despite the excellent psychometric properties of FMA-UL, WMFT, and ARAT, all these tools require a considerable amount of time and are resource-intensive due to their comprehensive nature and need for manual administration. ¹⁹ In particular, FMA-UL requires longer than 30 minutes to complete the test and needs material resources and/or tools including a standardized chair and/or desk to execute the same. ²⁰ Furthermore, administration of these said measures can be exhaustive, cumbersome, and often impractical for bedside evaluation. The time taken to administer a tool significantly influences its probability of regular usage in clinical practice. Hence, tools that take a quicker time are more likely to be utilized. ³

Emerging evidence suggests that the inclusion of non-contact gesture movements (e.g., salute and hand waving gesture) and contact-grasping (e.g., grasping a small glass) would strengthen the representativeness and comprehensiveness of evaluation of UL movements of daily life. ^{2 , 21} In addition, analysis of gesture and grasp movements can demonstrate task-specific and impairment-specific characteristics. ²¹ In line with that, we propose a conceptual framework for the clinical utility of day-to-day movement tasks such as hand gesture movements, grasping movements, ²² and rhythmic finger tapping ²³ in evaluating the UL function in stroke. Although previous studies have quantified the impairments in hand gestures, grasping, and finger tapping, these studies primarily employed expensive quantifiable technology to investigate such as wearable gloves for hand gesture recognition, and ultrasound-based motion analyzer for kinetic and kinematic analysis of grasping. ^{22 , 24 , 25} Evidence suggests that the finger-tapping test is a useful tool in predicting recovery in stroke survivors. ^{26 , 27} Currently, there is no simple, qualitative, resource, and time-efficient tool that could be quickly administered at the bedside to evaluate UL function in stroke survivors.

Therefore, the primary aim of the present study was to develop a bedside tool based on day-to-day movement tasks that can be administered with ease, accuracy, minimal time consumption, and less exhaustion to measure the UL function following stroke. The secondary aim was to assess the concurrent validity of the new bedside tool.

The study comprised of 2 phases 1) scale development and content validity verification 2) concurrent validity determination with WMFT. After receiving approval from the Research and Institutional Ethics Committee of Kasturba Medical College, Mangalore (IEC KMC MLR 1/2022/15) on 19/01/2022, a dual-phasic study containing qualitative and cross-sectional elements was undertaken in teaching hospitals affiliated with Kasturba Medical College, Mangalore, from February 2022 to January 2023. The study adhered to the ethical principles of the Declaration of Helsinki for research involving human participants. The qualitative phase included tool development, whereas the cross-sectional phase focused on tool validation. Purposive sampling was implemented for participant recruitment during cross-sectional phase. The study included adult participants (>18 years of age) diagnosed with primary infarction/hemorrhagic stroke and hemiparesis of the upper limb (UL). Exclusion criteria of the study were i) other neurological disorders, ii) severe cognitive deficits (Montreal Cognitive Assessment score < 24), iii) perceptual dysfunctions, and iv) pre-existing UL musculoskeletal conditions affecting testing.

In the current study, evidence is provided for the contention that day-to-day movement gestures, grasping activities, and rhythmic wrist and finger movements constitute a significant tool for the evaluation of UL function in stroke survivors. Previous research primarily focused on investigating the therapeutic efficacy of gesture, grasping, and finger-tapping movements to enhance UL function using quantitative and expensive methods. ^{2 , 22} Nonetheless, there is an apparent significant gap in the literature regarding the development and validation of a qualitative bedside tool utilizing daily gesture, grasping, and finger tapping movements for evaluating UL function in stroke survivors. Existing tools in assessment of shoulder, elbow, wrist, and hand motor impairment require specific materials, training, and excessive amount of time. Consequently, a simple, inexpensive, resource (no resources) and time-efficient (<10 mins) Bedside Upper Limb Evaluation Tool (BUFET) was developed and validated with methodological study design. Such a qualitative bedside tool that can be implemented in clinical, research, or home settings could be a critical component in stroke rehabilitation.

Evaluation of UL and hand function is pivotal for the comprehensive rehabilitation of stroke survivors. The newly developed BUFET serves as a qualitative instrument that can be efficiently administered at the bedside. This tool facilitates the observation of intricate patterns in shoulder, elbow, hand, and wrist movements during the execution of gestures, grasping, and fine finger movements. According to Michael Roth, symbolic hand gestures are predominantly upper arm and hand movements, conceptualized as originating from ergotic hand movements associated with object manipulation and epistemic hand movements related to sensing activity. ³³ In general, hand orientation assumed by the grasping hand depends on the initial hand position, location, shape, and orientation of the object to be grasped. ^{34 , 35} However, stroke survivors often exhibit impaired gesture imitation, influencing the performance of specific arm and hand segments (limb apraxia). ²¹

Kinematic studies have indicated that complex hand gestures and grasp movements in stroke survivors are associated with altered joint rotation patterns, hand orientations, and impaired inter-joint coordination of grasp and twist. ^{2 , 7} Evidence also suggests that impaired hand gesture imitation is linked to posterior lesions in the left inferior parietal lobule (LIPL) and temporal-parietal-occipital junction (TPOJ), while impaired finger gesture imitation is associated with lesions in the inferior frontal gyrus (IFG). ^{36 , 37} These brain regions are responsible for motor planning, coordination, and the integration of sensory-motor information. ⁷

Consequently, prompt qualitative movement analysis of gestures, grasping, and fine finger movements using BUFET at the bedside empowers the examiner to raise clinical suspicion regarding the potential location of brain lesions in stroke survivors. This tool facilitates early and timely interventions. In particular, the qualitative assessment focused on UL motor function can reveal distinctive patterns that correlate with the left inferior parietal lobule (LIPL) and temporal-parietal-occipital junction (TPOJ), enabling differentiation between stroke groups and offering valuable insights into the functional abilities of stroke survivors. Furthermore, it may provide indications of specific brain lesion types, distinguishing between posterior (LIPL) and anterior (IFG) lesions.

The BUFET covers a wide range of UL, hand, and finger movements. The first component-salute evaluates the ability to produce a movement pattern away from the typical attitude of the affected limb. ³⁸ The second and the third components (holding the nose and hand waving, respectively) help to assess the quality of control of shoulder flexors and external rotators which are reported to be considerably impaired among stroke subjects. ³⁹ Also, the second item (holding the nose) reflecting hand-to-mouth function is reported to be a significant method to evaluate UL in subjects with stroke. ⁴⁰ The functional ability of the intermediate joint (i.e., elbow), to achieve complete flexion is also tested in the first and second components while the elbow extension is tested in the third component. Levin et al emphasized that the movement amplitudes at the shoulder and elbow joints were significantly impaired during the excursion of the hemiparetic arm. ³⁵ In particular, during reach-out tasks, effective shoulder movements with inter-joint coordination are paramount. ⁴¹ Hence, hand waving has been included as a third component to evaluate shoulder function.

Wrist circumduction movement is usually described as flexion-extension motion in function of radio-ulnar deviation. Most daily activities of life can be performed through an arc from 10° flexion to 35° extensions. Evidence suggests that static flexion posture of finger significantly influences wrist circumduction with a linear relationship between wrist and finger movements. ⁴² This phenomenon is particularly implicated in wrist drop observed among people with unilateral stroke. A Rasch model analysis of the psychometric properties of wrist and hand subscales of FMA-UL in stroke reported a higher/large positive factor loading (0.846) for wrist circumduction representing the unidimensional construct of UL and hand motor function. ⁴³ Thus, inclusion of clockwise and anti-clockwise stirring action of the wrist as one of the items demonstrated that BUFET is unidimensional. Furthermore, reduced selectivity of the muscles that control isolated index finger extension, a deficit in the ability to perform isolated finger extension, has also been studied. ⁴⁴ Hence, inclusion of pointing the index finger upwards with the wrist in extension is considered significant.

Maximum grip force is generated with the wrist held in extension, ²² and lack of recovery of grasp efficiency may suggest the inability of the descending pathways to control the distal muscles. ⁴⁵ Additionally, the radial aspect of the hand plays a significant role in fine motor tasks such as gripping, which require greater dexterity and strength. Liu et al. stated that the thumb, index, and middle fingers that are controlled by the radial aspect of the hand are more prone to impairment compared to other fingers. ⁴⁶ Due to these reasons, the evaluation of the grip strength through the radial aspect is considered.

The opposition of thumb is essential for daily activities like picking up small objects. The opposition was noted to be reduced in stroke subjects when compared to healthy. ⁴⁷ Nijland et al. reported that the ability to extend the finger within 72 hours post-stroke can predict functional recovery in the hemiplegic arm at 6 months. ⁴⁸ While attempting to move a specific digit, inappropriate contractions of muscles in other digits were noted among stroke subjects. ⁴⁴ Prior research also stated an increased level of motor impairment with ulnar fingers i.e., middle, ring, and little finger. ⁴⁹ Since specific digit(s) movements are likely to be impaired in stroke subjects pointing the index finger upwards and gesturing the number “3” are included.

Studies have reported impaired thumb movements and reduced velocity in finger flexion movements among stroke subjects. ⁵⁰ To evaluate thumb and middle finger control, the snapping action of the finger that requires quick flexion of the middle finger against the thumb is selected as a component. In addition, finger abduction/adduction was reported to be greatly impaired compared to flexion/extension. ⁴⁴ Thus, BUFET included the scissoring action of the index and middle fingers as a test item to evaluate the finger abduction and adduction movements. Reduced individual finger movement is associated with greater hand impairment and the same study also reported unwanted extra finger movements during finger individuation that correlated with lower ARAT and Moberg Pick-Up Test scores. ⁵¹ Hence, finger-tapping that assesses individual movement of the digits is incorporated.

WMFT assesses the functional ability of the UL. Out of the 15 items, 6 components (40%) focus exclusively on the proximal joints. Contrary to that, 3 components of BUFET (25%) assess proximal control, thus ensuring a larger proportion of the scale to focus on diverse hand functions. All the test components of BUFET were administered at ease at the bedside. The BUFET required an average of 10 minutes to complete its administration when compared to the 30–35-minute requirement for WMFT. ^{13 , 52}

Our results for the correlation analysis between BUFET and WMFT revealed a high correlation coefficient (r = 0.937, p<0.001) which suggest that both tools measure similar, unidimensional construct. The BUFET also demonstrated a high internal consistency with Cronbach’s alpha value of 0.948 ( p<0.001) which is consistent with the alpha scores of WMFT-0.92, ³¹ FMA-U -0.98, ⁵³ and ARAT -0.98. ⁵⁴ The results imply that the BUFET is capable of detecting motor functions nearly identical to the WMFT. In addition to the above, it also suggests that BUFET can be used as an easy-to-administer bedside outcome measure for UL function post-stroke.

DP was the principal investigator (PI) for this study. The conceptualization and the initial development of tool were by the corresponding author (AMJ) who holds the copyright (Reg # L-137026/2023) for the proposed tool. The BUFET is made freely available for teaching and clinical purpose. For research and publication purpose, it is mandatory to credit the corresponding author with relevant citation. Supervision of the trial and the data collection were performed by AN, AJP, and VP. The study was designed, and the data analysis was executed by PM and SA. All the authors equally contributed to the preparation and editing of this manuscript.

Approval was obtained from the Research and Institutional Ethics Committee of Kasturba Medical College, Mangalore (IEC KMC MLR 1/2022/15) on 19/01/2022. The study adhered to the ethical principles of the Declaration of Helsinki for research involving human participants.

Appropriate written informed consent, approved by the Institutional Ethics Committee, was obtained from the study participants. Consent was also taken from the model for animated photographs used in the BUFET description.

Underlying Data: Bedside Upper Limb Functional Evaluation Tool (BUFET)