Maciej Kochman
Marta Kasprzak
Aleksandra Kielar- 1Department of Clinical Physiotherapy in Musculoskeletal Disorders, Institute of Physiotherapy, Faculty of Health Sciences and Psychology, Collegium Medicum, University of Rzeszów, Rzeszów, Poland
- 2Faculty of Medicine, Collegium Medicum, University of Rzeszów, Rzeszów, Poland
Stroke survivors often experience sensory, cognitive, and motor consequences with gait disorders as a common problem. Therefore, there is a need for a deeper understanding of how neurological deficits affect the functioning of patients after a stroke. Current scientific literature lacks research on proprioception impairment, and gait recovery after stroke. In this narrative review, we discussed and summarized the current knowledge about the abnormal post-stroke gait pattern, the role of proprioception in motor control, methods of proprioception assessment, and the association between abnormal gait and proprioception deficit in stroke survivors. The present findings must be interpreted with some caution as current evidence is limited, as well as the correlation does not imply causation and might be underestimated by attributes of current tests for proprioception and motor function. Further studies are needed to better explain the mechanisms behind proprioception deficits and their association with functional recovery, as well as to investigate the cause-effect relationship.
1 Introduction
Stroke is a serious health problem exploiting a significant proportion of health care system budgets worldwide (1). The World Health Organization (WHO) indicates that stroke is the incoming epidemic of the 21st century and a further increase in stroke rates is expected worldwide, especially in younger patients (2). According to the World Stroke Organization (WSO), stroke remains the second most common cause of death and the third most common cause of combined death and disability expressed by disability-adjusted life-years lost (DALYs) worldwide (3). The definition of stroke includes rapidly developing clinical symptoms of focal or global disturbance of cerebral function, while signs last at least 24 h or lead to death and their cause is no other than vascular origin (4).
Despite a decline in stroke mortality rates, the prevalence of people living with stroke consequences has risen due to an increasing and aging population. This leads to a greater need for long-term rehabilitation (5). People after a stroke often experience sensory, cognitive, and motor consequences (6). Gait disorders are a common problem in stroke survivors as they constitute one of the main functional limitations that affect the quality of life and increase the risk of falls. Moreover, independent walking is an important factor in overall health and one of the fundamental goals of stroke rehabilitation (7). Stroke survivors may have different gait patterns depending on the variety of sensorimotor disorders (8). However, the relationship between sensory impairment and other impairments or functional deficits following a stroke is unclear and has not been widely explored in the literature. Moreover, despite the expectation that sensory or motor deficits may be associated with stroke severity due to lesion size and location, the association between these impairments is still not well understood (9). Previous studies showed that lesions in the supramarginal gyrus, arcuate fasciculus, and Heschl’s gyrus are linked to poor proprioceptive recovery. Also, proprioception impairment is common and persistent after stroke, particularly in the cortical and subcortical lesions (10).
Due to the constantly increasing incidence of stroke and the increasing number of people living with its consequences, there is a need for a deeper understanding of how neurological deficits, including proprioception deficit, affect the functioning of patients after a stroke. As this topic is underexplored in the scientific literature, we were prompted to perform this narrative literature review, which, according to the best knowledge of authors, is the very first review providing a comprehensive understanding of the role of proprioception in post-stroke gait recovery. In this review, we present and summarize the current knowledge about the abnormal post-stroke gait pattern, role of proprioception in motor control, methods of proprioception assessment, and the association between abnormal gait and proprioception deficit in stroke survivors.
2 Hemiplegic gait and its characteristics
People after a stroke usually present various neurological deficits, such as motor, sensory, cognitive, or perceptual impairments. One of the major post-stroke disorders is a motor deficit manifesting in contralateral hemiparesis to the cerebrovascular incident, which decreases the capacity of affected limbs to initiate and control movements and maintain balance, resulting in abnormal gait patterns (11). Abnormal gait is very common after stroke as more than 80% of stroke survivors suffer from varying degrees of gait abnormalities, and about 25% of them have an enduring impairment requiring full physical assistance, despite long-term rehabilitation (12).
A characteristic gait pattern in stroke patients is the so-called hemiparetic (or hemiplegic) gait. This gait pattern is characterized by specific temporal and spatial patterns, including reduced cadence, reduced walking speed, increased step width, increased duration of the double stance phase, and asymmetric loading of a single lower limb. After a stroke, the affected limb shows a prolonged duration of the swing phase, caused by a deficit of the force required to move forward, and a shortened duration of the stance phase. As a result, a shortened duration of the swing phase and an increased duration of the stance phase are observed in the non-affected lower limb (11, 13, 14).
Moreover, hemiplegic gait is also characterized by asymmetry and shortened step length of the non-affected lower limb, compared to the gait of healthy individuals (14, 15). Also, the kinematic parameters of hemiparetic gait show increased movement of the trunk in the lateral and sagittal planes, greater movement of the upper part of the trunk in the transverse plane, reduced interphase rotation of the upper and lower parts of the trunk, and reduced stability and symmetry compared to non-pathological gait. Unlike the limbs, the functioning of the trunk after a stroke is impaired bilaterally. Both the part of the trunk on the paretic side and the part of the trunk on the side indirectly affected after a stroke are characterized by a reduced level of activity and reduced synchronization of its muscle work (14, 16).
Muscle strength deficits in the trunk muscles affect its balance and coordination and cause changes in the biomechanics of gait. Studies indicate that weakening of the trunk extensors and flexors and associated balance disorders contribute to reduced functional independence in walking and transfers getting up from a sitting position, as well as gait speed (17). Also, walking speed is mainly influenced by the weakening of the hip flexors and knee extensors, while gait symmetry is significantly influenced primarily by the degree of spasticity of the ankle flexors, however, the ankle flexors also affect walking speed (18–20).
Foot clearance is an important gait parameter that affects tripping during the swing phase, which is a serious cause of falls. In healthy subjects, foot clearance is determined by hip and knee joint flexion and ankle dorsiflexion (21, 22). In patients with hemiplegic gait, during the swing phase, flexion movement of the lower limb is impaired distinguishing “foot drop” and “stiff-knee gait” among them, which cause characteristic movements such as hip hiking and circumduction (21, 23, 24). These compensatory movements are performed to achieve better foot clearance to compensate for the reduced lower limb flexion (25). Foot drop is one of the most common post-stroke disorders affecting the gait of people after stroke, which is associated with the weakening or lack of voluntary control of the ankle dorsal flexors and/or increased spasticity of the plantar flexors (26–28). It disturbs the dorsal flexion of the foot during the swing phase and causes disorders in accepting and transferring body weight in the initial foot contact and the stance phases (27). Approximately 60% of stroke survivors with gait impairment experience stiff-knee gait, also known as stiff-legged gait. The definition of this gait pattern in the literature varies depending on the source (29). However, it is characterized by reduced knee flexion during the swing phase of the gait cycle (12, 29, 30).
3 Proprioception and its role in motor control
Proprioception is the sensation of body position and movement and it is essential for movement control as it provides inputs to internal models that link sensory signals with motor commands (31, 32). It involves signals from mechanoreceptors (transducers that transform mechanical stimuli into action potentials) positioned in muscles, tendons, and joint capsules (proprioceptors), whereas information received from cutaneous mechanoreceptors (cutaneous stretch receptors) related to tactile sensations, is regarded as additional sensory sources completing proprioceptive inputs (31). Muscle proprioceptors include muscle spindles, which respond to the stretching of muscle fibers, and Golgi tendon organs. Pacinian and Ruffini corpuscles are considered joint receptors because of their strong association with ligaments, but they can be observed throughout the body. Skin proprioception is also associated with the same group of sensory receptors. However, they are embedded in the skin and deep connective tissues covering mobile joints or muscles. Sensory neurons, including Meissner and Merkel cells, are activated by movement or touch on the skin (33).
All collected proprioceptive information is processed in the spinal cord, brain stem, higher cortical centers and subcortical cerebral nuclei, and cerebellum. This data is then used in daily activities, exercises, and sports (34) and it allows one to maintain posture, maneuver in the dark, and manipulate objects out of sight. Moreover, in people with correct proprioception, eliminating visual information still allows them to determine the position and movement of individual body parts (35). It has also been shown that information from both the joint and the skin is related to the sense of upright position, which affects balance. This also plays a critical role in providing feedback on the distribution of body weight on individual limbs (35, 36). Proprioception disorders can occur as a result of improper functioning of the musculoskeletal system due to injury, aging, or neurological disorders such as stroke (36, 37).
4 Proprioception assessment and its impact on gait
Due to the crucial role of proprioception in the human body, it is important to use specific methods and tools to assess it. Various techniques have been introduced in the literature to investigate proprioceptive mechanisms. Three primary methods for evaluating proprioception are: (1) TTDPM (threshold to detection of passive motion), (2) JPR (joint position reproduction or joint position matching), and (3) AMEDA (active movement extent discrimination assessment) (38) (Figure 1).
Figure 1. Methods of proprioception assessment.
A standard TTDPM assessment includes indicating the first detection of passive motion at the joint by a blindfolded individual. This outcome is measured by the degree of the joint movement or the time elapsed before the individual indicates the detection of movement. Another variable is the detection of the movement direction of the examined body part (e.g., flexion or extension) (39).
In the JPR assessment, a blindfolded individual is asked to recreate a position of a joint angle that they previously experienced using their ipsilateral or the contralateral limb. The proprioceptive sensitivity is indicated by the magnitude of matching errors, as it is believed that subjects making significant position-matching errors are somehow proprioceptively deficient (40). Three methods of JPR assessment have been described in the literature: IJPR (ipsilateral JPR) and two CJPR (contralateral) assessments. In the IJPR assessment, the target position of the joint is passively or actively introduced to the individual for a few seconds prior. After that, the examined limb returns passively or actively to the initial start position. Then the participant is asked to recreate the target position of the joint either by pressing the stop button when the same limb is being moved passively or by moving the joint to the target position if the motion reproduction is active. In CJPR assessments, one method is identical to the JPR except for using the contralateral limb when recreating the target position. In the second CJPR assessment, instead of returning to the start position, the examined limb remains in the target position and the contralateral limb is required to recreate that position (38, 41).
Unlike the previous methods, the AMEDA assessment is performed in a standing position in an unconstrained weight-bearing stance that mimics the conditions that proprioception would encounter outside the laboratory in daily life (42). This method indicates an individual’s somatosensory function by assessing their sensitivity to detect small differences in the angular position of ankle inversion (43). In this method, the participants are asked to indicate in absolute terms the angle at which the plate is displaced from the horizontal (44). This approach provides ankle movement discrimination scores obtained with a single stimulus that utilizes a fixed set of stimuli with one variable stimulus value presented on each trial (45).
Although the AMEDA assessment demonstrates good reliability in healthy adults, it may be impacted by various factors such as chronic ankle instability (46), lapses in attention, or disengagement from the task (47). Despite its established utility for discriminating between participant groups, concerns have been raised about using the AMEDA to classify proprioception acuity at an individual level. Issues included poor test–retest reliability, a small number of stimuli, task difficulty, and a lack of sequencing effects in the analysis (44). According to Waddington and Witchalls, better reliability in AMEDA assessments is achieved with a shorter, 25-response protocol rather than more traditional 50-response protocol, as the shorter version prevents disengagement or inattention (47). Additionally, as noted by Krewer et al. (48), AMEDA measurements do not indicate the proprioception level of a specific joint. Instead, they represent a “multi-modal, multi-joint measure of a multi-segment posture” (48).
To better understand and evaluate the mechanism of proprioception in stroke survivors’ rehabilitation it is essential to use accurate and sensitive assessments and tools. In clinical settings, proprioception assessments were traditionally performed on simple subjective observation-based tests. Usually, the examiner moves the patient’s finger or toe while patients with eyes closed were asked to report the position of this body part. These tests, however, present poor reliability, lack resolution, and display “ceiling effects.” The above-outlined challenges prompted some research groups to design standardized and reliable clinician-administered questionnaires such as the Nottingham Sensory Assessment or Rivermead Assessment of Somatosensory Performance (RASP) (49). Moreover, recently automated and instrumented measurement tools such as electronic goniometers, smartphones, and robot-assisted technologies, have been introduced to assess proprioception impairment (49, 50). Robot-assisted proprioception assessment allows to generation of a rich dataset of kinematic data quantifying impairments that may be difficult to assess by clinical observation-based tests. This large volume of data may be useful in predicting outcomes and planning physiotherapy programs in many conditions, such as stroke (49, 51).
Somatosensory impairment, its nature, and its extent after stroke are not yet fully understood. It is known that it is common after stroke with the prevalence varying from 11 to 60% depending on the heterogeneity of populations, the number of somatosensory modalities, and body parts assessed (52, 53). Among stroke survivors with somatosensory impairment, about 34 to 64% of them suffer from proprioception impairment.
Stroke severity is the main factor affecting somatosensory impairment and initial somatosensory impairment is a great predictive factor for recovery. Moreover, the somatosensory assessment provides useful prognostic information for the functional status of patients. Despite that, the scientific literature lacks research on somatosensory, especially proprioception, impairment, and recovery after stroke (52). On the other hand, the results of present studies indicate the controversies on the impact of sensory function on gait performance, which have been partly linked to the various methods used in assessing sensory function (54). Another reason is that the neuroanatomical injury caused by stroke varies greatly in both location and severity (55). Unfortunately, the understanding of the brain regions involved in processing and lateralization of the proprioceptive signals is still not well explored. It is known that each limb is controlled by contralateral regions of the brain (56). However, some studies suggest that brain activity related to proprioceptive tasks is lateralized, with the right hemisphere being more dominant, regardless of limb dominance (57). Although there is some evidence supporting this lateralization, it is limited and restricted to the upper limbs. For the lower limbs there is some evidence that the non-dominant side is preferred for position-matching tasks. However, contradictory findings regarding the impact of side dominance in lower limb position matching create uncertainty in this area of research (56).
Moreover, after stroke, somatosensory structures may be impacted at some times or preserved at others. Also, proprioception assessment depends on cognitive abilities such as attention and working memory, which are frequently affected in stroke survivors and confounded by fatigue leading to further proprioception assessment variability (55).
A meta-analysis proved a correlation between proprioceptive impairment and motor deficits after stroke. The subgroup analysis revealed multiple factors with positive contributions to this relationship such as proprioception assessed in the axial segment under weight-bearing conditions, proprioception assessed by ipsilateral matching task, and motor function analyzed within ICF domains including movement function, activity independence, and activity performance (58). It was also proved that touch and proprioception are intimately integrated and their impairment affects functional activity. This may suggest that instead of individual sensory retraining, functional task training of both of these impairments may be a more effective treatment (59).
It was observed that in the acute phase of stroke rehabilitation, somatosensory impairment was related to lower functional status, poorer rehabilitation outcomes, and longer length of hospital stay (53). Another study proved that the interaction of knee extensor strength and proprioception on the affected side is strongly linked to gait independence in subacute stroke patients (60).
In the chronic phase of stroke rehabilitation, knee and ankle joint position sense is not related to gait performance, however, ankle proprioception was an important contributor to gait speed and stride length, which supports the importance of proprioception in the decision-making process about changing the gait pattern in stroke survivors (54). Another study also showed that ankle proprioception is the main indicator of balance impairment in stroke survivors with balance disorders in the chronic recovery stage affecting walking velocity and overall gait efficiency. This may demonstrate that ankle proprioception should be included in post-stroke lower limb rehabilitation (36). The relationship between proprioception deficit and gait function in a specific stroke recovery phase has been presented in Figure 2.
Figure 2. The relationship between proprioception deficit and gait function after stroke.
Interestingly, proprioception deficit was also observed on the unaffected leg in chronic stroke patients which suggests a possible contribution of peripheral mechanisms (61).
5 Summary and future directions
The current understanding of proprioception and its impact on gait function in individuals after stroke remains limited. The present findings should be interpreted with caution, as correlation does not imply causation and may be confounded by limitations inherent in current assessments of proprioception and motor function.
Additional research is necessary to elucidate the cause-and-effect relationships involved and to clarify the mechanisms underlying proprioceptive deficits and their association with functional recovery.
In particular, future research should aim to deepen our understanding of the neuroanatomical foundations of proprioception, including the involvement of specific cortical centers in each cerebral hemisphere. Further research should also investigate whether similar right hemisphere lateralization and non-dominant side preference for proprioception are evident among individuals with left-limb or mixed-limb dominance. Advances in neuroimaging and neurophysiological techniques could provide valuable insights into how various brain regions contribute to proprioceptive processing and recovery following stroke.
Furthermore, targeting both proprioceptive and motor impairments simultaneously may offer a more effective approach to post-stroke rehabilitation. The integration of robotic technologies holds promise for the development of reliable and sensitive proprioceptive assessment tools. Developing and implementing more standardized, reproducible, and accurate devices is essential to quantify proprioceptive function and monitor changes over time. Such advancements would improve diagnostic precision and consequently enable more personalized and targeted rehabilitation strategies.
Author contributions
MKa: Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing. MKo: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. AK: Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing.
Funding
The author(s) declare that no financial support was received for the research and/or publication of this article.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The authors declare that no Gen AI was used in the creation of this manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1. Ojaghihaghighi, S, Vahdati, SS, Mikaeilpour, A, and Ramouz, A. Comparison of neurological clinical manifestation in patients with hemorrhagic and ischemic stroke. World J Emerg Med. (2017) 8:34–8. doi: 10.5847/wjem.j.1920-8642.2017.01.006
2. Sarikaya, H, Ferro, J, and Arnold, M. Stroke prevention - medical and lifestyle measures. Eur Neurol. (2015) 73:150–7. doi: 10.1159/000367652
3. Feigin, VL, Brainin, M, Norrving, B, Martins, S, Sacco, RL, Hacke, W, et al. World stroke organization (WSO): Global stroke fact sheet. Int J Stroke. (2022) 17:18–29. doi: 10.1177/17474930211065917
4. Bertani, R, Melegari, C, de Cola, MC, Bramanti, A, Bramanti, P, and Calabrò, RS. Effects of robot-assisted upper limb rehabilitation in stroke patients: a systematic review with meta-analysis. Neurol Sci. (2017) 38:1561–9. doi: 10.1007/s10072-017-2995-5
5. Stinear, CM, Lang, CE, Zeiler, S, and Byblow, WD. Advances and challenges in stroke rehabilitation. Lancet Neurol. (2020) 19:348–60. doi: 10.1016/S1474-4422(19)30415-6
6. Mansfield, A, Inness, EL, and Mcilroy, WE. Stroke In: Handbook of clinical neurology : Elsevier (2018). 205–28.
7. Selves, C, Stoquart, G, and Lejeune, T. Gait rehabilitation after stroke: review of the evidence of predictors, clinical outcomes and timing for interventions. Acta Neurol Belg. (2020) 120:783–90. doi: 10.1007/s13760-020-01320-7
8. Geerars, M, Minnaar-van Der Feen, N, and Huisstede, BMA. Treatment of knee hyperextension in post-stroke gait. A systematic review. Gait Posture. (2022) 91:137–48. doi: 10.1016/j.gaitpost.2021.08.016
9. Sullivan, JE, and Hedman, LD. Sensory dysfunction following stroke: incidence, significance, examination, and intervention. Top Stroke Rehabil. (2008) 15:200–17. doi: 10.1310/tsr1503-200
10. Findlater, SE, Hawe, RL, Semrau, JA, Kenzie, JM, Yu, AY, Scott, SH, et al. Lesion locations associated with persistent proprioceptive impairment in the upper limbs after stroke. Neuroimage Clin. (2018) 20:955–71. doi: 10.1016/j.nicl.2018.10.003
11. Maje, AU, and Ibrahim, AA. Effectiveness of an 8-week overground walking with paretic lower limb loading on spatiotemporal gait parameters and motor function among chronic stroke survivors: a study protocol for a randomised controlled trial. Trials. (2023) 24:124. doi: 10.1186/s13063-022-07057-3
12. Lee, J, Akbas, T, and Sulzer, J. Hip and knee joint kinematics predict quadriceps hyperreflexia in people with post-stroke stiff-knee gait. Ann Biomed Eng. (2023) 51:1965–74. doi: 10.1007/s10439-023-03217-x
13. Lee, HS, Ryu, H, Lee, SU, Cho, JS, You, S, Park, JH, et al. Analysis of gait characteristics using hip-knee Cyclograms in patients with hemiplegic stroke. Sensors. (2021) 21:7685. doi: 10.3390/s21227685
14. Wang, Y, Mukaino, M, Ohtsuka, K, Otaka, Y, Tanikawa, H, Matsuda, F, et al. Gait characteristics of post-stroke hemiparetic patients with different walking speeds. Int J Rehabil Res. (2020) 43:69–75. doi: 10.1097/MRR.0000000000000391
15. Lewek, MD, and Randall, EP. Reliability of spatiotemporal asymmetry during Overground walking for individuals following chronic stroke. J Neurol Phys Ther. (2011) 35:116–21. doi: 10.1097/NPT.0b013e318227fe70
16. Van Criekinge, T, Saeys, W, Hallemans, A, Velghe, S, Viskens, PJ, Vereeck, L, et al. Trunk biomechanics during hemiplegic gait after stroke: a systematic review. Gait Posture. (2017) 54:133–43. doi: 10.1016/j.gaitpost.2017.03.004
17. Aguiar, LT, Camargo, LBA, Estarlino, LD, Teixeira-Salmela, LF, and Faria, CDCM. Strength of the lower limb and trunk muscles is associated with gait speed in individuals with sub-acute stroke: a cross-sectional study. Braz J Phys Ther. (2018) 22:459–66. doi: 10.1016/j.bjpt.2018.03.001
18. Cramp, MC, Greenwood, RJ, Gill, M, Rothwell, JC, and Scott, OM. Low intensity strength training for ambulatory stroke patients. Disabil Rehabil. (2006) 28:883–9. doi: 10.1080/09638280500535157
19. Hsu, A-L, Tang, P-F, and Jan, M-H. Analysis of impairments influencing gait velocity and asymmetry of hemiplegic patients after mild to moderate stroke11No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors(s) or upon any organization with which the author(s) is/are associated. Arch Phys Med Rehabil. (2003) 84:1185–93. doi: 10.1016/S0003-9993(03)00030-3
20. Wist, S, Clivaz, J, and Sattelmayer, M. Muscle strengthening for hemiparesis after stroke: a meta-analysis. Ann Phys Rehabil Med. (2016) 59:114–24. doi: 10.1016/j.rehab.2016.02.001
21. Matsuda, F, Mukaino, M, Ohtsuka, K, Tanikawa, H, Tsuchiyama, K, Teranishi, T, et al. Analysis of strategies used by hemiplegic stroke patients to achieve toe clearance. Jpn J Compr Rehabil Sci. (2016) 7:111–8. doi: 10.11336/jjcrs.7.111
22. Moosabhoy, MA, and Gard, SA. Methodology for determining the sensitivity of swing leg toe clearance and leg length to swing leg joint angles during gait. Gait Posture. (2006) 24:493–501. doi: 10.1016/j.gaitpost.2005.12.004
23. Bethoux, F, Rogers, HL, Nolan, KJ, Abrams, GM, Annaswamy, TM, Brandstater, M, et al. The effects of peroneal nerve functional electrical stimulation versus ankle-foot orthosis in patients with chronic stroke: a randomized controlled trial. Neurorehabil Neural Repair. (2014) 28:688–97. doi: 10.1177/1545968314521007
24. Martin, KD, Polanski, W, Schackert, G, and Sobottka, SB. New therapeutic option for drop foot with the ActiGait peroneal nerve stimulator—a technical note. World Neurosurg. (2015) 84:2037–42. doi: 10.1016/j.wneu.2015.06.074
25. Stanhope, VA, Knarr, BA, Reisman, DS, and Higginson, JS. Frontal plane compensatory strategies associated with self-selected walking speed in individuals post-stroke. Clin Biomech. (2014) 29:518–22. doi: 10.1016/j.clinbiomech.2014.03.013
26. Chisholm, AE, Perry, SD, and McIlroy, WE. Correlations between ankle–foot impairments and dropped foot gait deviations among stroke survivors. Clin Biomech. (2013) 28:1049–54. doi: 10.1016/j.clinbiomech.2013.09.007
27. Schifino, G, Cimolin, V, Pau, M, da Cunha, MJ, Leban, B, Porta, M, et al. Functional electrical stimulation for foot drop in post-stroke people: quantitative effects on step-to-step symmetry of gait using a wearable inertial sensor. Sensors. (2021) 21:921. doi: 10.3390/s21030921
28. Sheffler, LR, and Chae, J. Hemiparetic Gait. Phys Med Rehabil Clin N Am. (2015) 26:611–23. doi: 10.1016/j.pmr.2015.06.006
29. Chantraine, F, Schreiber, C, Pereira, JAC, Kaps, J, and Dierick, F. Classification of stiff-knee gait kinematic severity after stroke using retrospective k-means clustering algorithm. J Clin Med. (2022) 11:6270. doi: 10.3390/jcm11216270
30. Campanini, I, Merlo, A, and Damiano, B. A method to differentiate the causes of stiff-knee gait in stroke patients. Gait Posture. (2013) 38:165–9. doi: 10.1016/j.gaitpost.2013.05.003
31. Henry, M, and Baudry, S. Age-related changes in leg proprioception: implications for postural control. J Neurophysiol. (2019) 122:525–38. doi: 10.1152/jn.00067.2019
32. Tuthill, JC, and Azim, E. Proprioception. Curr Biol. (2018) 28:R194–203. doi: 10.1016/j.cub.2018.01.064
33. Marasco, PD, and De Nooij, JC. Proprioception: a new era set in motion by emerging genetic and bionic strategies? Annu Rev Physiol. (2023) 85:1–24. doi: 10.1146/annurev-physiol-040122-081302
34. Röijezon, U, Clark, NC, and Treleaven, J. Proprioception in musculoskeletal rehabilitation. Part 1: basic science and principles of assessment and clinical interventions. Man Ther. (2015) 20:368–77. doi: 10.1016/j.math.2015.01.008
35. Proske, U, and Gandevia, SC. The proprioceptive senses: their roles in signaling body shape, body position and movement, and muscle force. Physiol Rev. (2012) 92:1651–97. doi: 10.1152/physrev.00048.2011
36. Cho, J-E, and Kim, H. Ankle proprioception deficit is the strongest factor predicting balance impairment in patients with chronic stroke. Arch Rehabil Res Clin Transl. (2021) 3:100165. doi: 10.1016/j.arrct.2021.100165
37. Clark, NC, Röijezon, U, and Treleaven, J. Proprioception in musculoskeletal rehabilitation. Part 2: clinical assessment and intervention. Man Ther. (2015) 20:378–87. doi: 10.1016/j.math.2015.01.009
38. Han, J, Waddington, G, Adams, R, Anson, J, and Liu, Y. Assessing proprioception: a critical review of methods. J Sport Health Sci. (2016) 5:80–90. doi: 10.1016/j.jshs.2014.10.004
39. Strong, A, Arumugam, A, Tengman, E, Röijezon, U, and Häger, CK. Properties of tests for knee joint threshold to detect passive motion following anterior cruciate ligament injury: a systematic review and meta-analysis. J Orthop Surg Res. (2022) 17:134. doi: 10.1186/s13018-022-03033-4
40. Goble, DJ. Proprioceptive acuity assessment via joint position matching: from basic science to general practice. Phys Ther. (2010) 90:1176–84. doi: 10.2522/ptj.20090399
41. Elangovan, N, Herrmann, A, and Konczak, J. Assessing proprioceptive function: evaluating joint position matching methods against psychophysical thresholds. Phys Ther. (2014) 94:553–61. doi: 10.2522/ptj.20130103
42. Antcliff, S, Welvaert, M, Witchalls, J, Wallwork, SB, and Waddington, G. Assessing proprioception in an older population: reliability of a protocol based on active movement extent discrimination. Percept Mot Skills. (2021) 128:2075–96. doi: 10.1177/00315125211029906
43. Dickson, TJ, Waddington, G, and Terwiel, FA. Snowsport experience, expertise, lower limb injury and somatosensory ability. J Sci Med Sport. (2019) 22:S17–21. doi: 10.1016/j.jsams.2018.08.005
44. Antcliff, S, Welvaert, M, Witchalls, J, Wallwork, SB, and Waddington, G. Using the active movement extent discrimination apparatus to test individual proprioception acuity: implications for test design. Percept Mot Skills. (2021) 128:283–303. doi: 10.1177/0031512520977683
45. Yang, N, Waddington, G, Adams, R, and Han, J. Joint position reproduction and joint position discrimination at the ankle are not related. Somatosens Mot Res. (2020) 37:97–105. doi: 10.1080/08990220.2020.1746638
46. Shi, X, Ganderton, C, Tirosh, O, Adams, R, EI-Ansary, D, and Han, J. Test-retest reliability of ankle range of motion, proprioception, and balance for symptom and gender effects in individuals with chronic ankle instability. Musculoskelet Sci Pract. (2023) 66:102809. doi: 10.1016/j.msksp.2023.102809
47. Waddington, G, and Witchalls, J. The protocol for active movement extent discrimination assessment (AMEDA) is reliable when shortened from 50 to 25 stimuli to reduce testing fatigue. Percept Mot Skills. (2024):00315125241304169. doi: 10.1177/00315125241304169
48. Krewer, C, van de Winckel, A, Elangovan, N, Aman, JE, and Konczak, J. Commentary on: “assessing proprioception: a critical review of methods” by Han et al. J Sport Health Sci. (2016) 5:91–2. doi: 10.1016/j.jshs.2015.11.001
49. Hossain, D, Scott, SH, Cluff, T, and Dukelow, SP. The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke. J Neuroeng Rehabil. (2023) 20:15. doi: 10.1186/s12984-023-01140-9
50. Al Saadawy, BO, Abdo, N, Embaby, E, and Youssef, AR. Validity and reliability of smartphones in measuring joint position sense among asymptomatic individuals and patients with knee osteoarthritis: a cross-sectional study. Knee. (2021) 29:313–22. doi: 10.1016/j.knee.2021.02.012
51. Rinderknecht, MD, Lambercy, O, Raible, V, Büsching, I, Sehle, A, Liepert, J, et al. Reliability, validity, and clinical feasibility of a rapid and objective assessment of post-stroke deficits in hand proprioception. J Neuroeng Rehabil. (2018) 15:47. doi: 10.1186/s12984-018-0387-6
52. Connell, L, Lincoln, N, and Radford, K. Somatosensory impairment after stroke: frequency of different deficits and their recovery. Clin Rehabil. (2008) 22:758–67. doi: 10.1177/0269215508090674
53. Sommerfeld, DK, and Von Arbin, MH. The impact of somatosensory function on activity performance and length of hospital stay in geriatric patients with stroke. Clin Rehabil. (2004) 18:149–55. doi: 10.1191/0269215504cr710oa
54. Lin, S-I. Motor function and joint position sense in relation to gait performance in chronic stroke patients. Arch Phys Med Rehabil. (2005) 86:197–203. doi: 10.1016/j.apmr.2004.05.009
55. Johnson, CA, Biswas, P, Tapia, R, See, J, Dodakian, L, and Chan, V. The weak relationship between ankle proprioception and gait speed after stroke a robotic assessment study. arXiv preprint arXiv. (2024), 2402. https://www.frontiersin.org/journals/human-neuroscience/articles/10.3389/fnhum.2023.969101/full
56. Strong, A, Grip, H, Arumugam, A, Boraxbekk, CJ, Selling, J, and Häger, CK. Right hemisphere brain lateralization for knee proprioception among right-limb dominant individuals. Front Hum Neurosci. (2023) 17:969101. doi: 10.3389/fnhum.2023.969101
57. Strong, A, Grip, H, Boraxbekk, CJ, Selling, J, and Häger, CK. Brain response to a knee proprioception task among persons with anterior cruciate ligament reconstruction and controls. Front Hum Neurosci. (2022) 16:841874. doi: 10.3389/fnhum.2022.841874
58. Yu, Y, Chen, Y, Lou, T, and Shen, X. Correlation between proprioceptive impairment and motor deficits after stroke: a meta-analysis review. Front Neurol. (2022) 12:688616. doi: 10.3389/fneur.2021.688616
59. Tyson, SF, Crow, JL, Connell, L, Winward, C, and Hillier, S. Sensory impairments of the lower limb after stroke: a pooled analysis of individual patient data. Top Stroke Rehabil. (2013) 20:441–9. doi: 10.1310/tsr2005-441
60. Fujita, T, Ohashi, Y, Kurita, M, Yamane, K, Yamamoto, Y, Sone, T, et al. Functions necessary for gait independence in patients with stroke: a study using decision tree. J Stroke Cerebrovasc Dis. (2020) 29:104998. doi: 10.1016/j.jstrokecerebrovasdis.2020.104998
Keywords: stroke, rehabilitation, physiotherapy, gait disorders, gait analysis, somatosensory disorders, proprioception, position sense
Citation: Kochman M, Kasprzak M and Kielar A (2025) The impact of proprioception impairment on gait function in stroke survivors: a comprehensive review. Front. Neurol. 16:1577919. doi: 10.3389/fneur.2025.1577919
Edited by:
Robert Nickl, Johns Hopkins University, United StatesReviewed by:
Luis Rafael Moscote-Salazar, Colombian Clinical Research Group in Neurocritical Care, ColombiaKai Guo, Institute of Biomedical Engineering and Technology (CAS), China
Copyright © 2025 Kochman, Kasprzak and Kielar. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Maciej Kochman, bWtvY2htYW5AdXIuZWR1LnBs