Clinical Measures for Tone Assessment in Adults with Central Nervous System Disorders—A Scoping Review in a Rehabilitation Context
Abstract
:1. Introduction
Research Questions
- Primary question:
- Secondary questions:
- i.
- What clinical conditions of the CNS were considered in the identified studies?
- ii.
- Which variable/concept is measured?
- iii.
- What procedures were used to test the concept identified?
2. Materials and Methods
2.1. Eligibility Criteria
- Population: adults (>19 years old) with CNS disorders;
- Concept: assessment of tone disorders;
- Context: clinical or rehabilitation.
2.2. Information Source
2.3. Selection of Evidence Sources
2.4. Data Extraction
2.5. Data Presentation
3. Results
4. Discussion
4.1. Clinical Measurement Instruments
4.2. Central Nervous System Disorder
4.3. Variable/Concept under Study and Test Procedures
4.4. Applications of the Research
- Accurate muscle tone assessment is crucial for making the most effective intervention decisions.
- In a clinical setting, assessing and understanding muscle tone enables physiotherapists to better analyse and establish appropriate interventions for patients with central nervous system disorders.
- Reaching a consensus on the conceptualization, interpretation, and measurement of results is essential to minimize subjective variations during clinical examinations. This contributes to effective communication among professionals and enhances decision-making for interventions.
- Testing procedures based on neurophysiological muscle tone characteristics are needed in order to improve understanding and clear conceptual definitions, which could provide necessary insights for a better approach in practical contact with patients for physiotherapy evaluations and consequent interventions.
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
- Ivanenko, Y.; Gurfinkel, V.S. Human Postural Control. Front. Neurosci. 2018, 12, 171. [Google Scholar] [CrossRef] [PubMed]
- Ganguly, J.; Kulshreshtha, D.; Almotiri, M.; Jog, M. Muscle Tone Physiology and Abnormalities. Toxins 2021, 13, 282. [Google Scholar] [CrossRef] [PubMed]
- Michielsen, M.; Vaughan-Graham, J.; Holland, A.; Magri, A.; Suzuki, M. The Bobath concept—A model to illustrate clinical practice. Disabil. Rehabil. 2019, 41, 2080–2092. [Google Scholar] [CrossRef] [PubMed]
- Rushworth, G. Spasticity and rigidity: An experimental study and review. J. Neurol. Neurosurg. Psychiatry 1960, 23, 99–118. [Google Scholar] [CrossRef] [PubMed]
- Shortland, A.P. Muscle tone is not a well-defined term. Dev. Med. Child Neurol. 2018, 60, 637. [Google Scholar] [CrossRef]
- Sunnerhagen, K.S.; Olver, J.; Francisco, G.E. Assessing and treating functional impairment in poststroke spasticity. Neurology 2013, 80, S35–S44. [Google Scholar] [CrossRef]
- de Noordhout, A.M.; Myressiotis, S.; Delvaux, V.; Born, J.D.; Delwaide, P.J. Motor and somatosensory evoked potentials in cervical spondylotic myelopathy. Electroencephalogr. Clin. Neurophysiol. 1998, 108, 24–31. [Google Scholar] [CrossRef]
- Lundy-Ekman, L. Neuroscience Fundamentals for Rehabilitation; Sunders Elsevier: Amsterdam, The Netherlands, 2018. [Google Scholar]
- Gurfinkel, V.S. Postural Muscle Tone. In Encyclopedia of Neuroscience; Binder, M.D., Hirokawa, N., Windhorst, U., Eds.; Springer: Berlin/Heidelberg, Germany, 2009; pp. 3219–3221. [Google Scholar]
- Shumway-Cook, A.; Woollacott, M.H. Motor Control: Translating Research into Clinical Practice; Wolters Kluwer, Lippincott Williams & Wilkins: Philadelphia, PA, USA, 2012. [Google Scholar]
- Latash, M.L.; Huang, X. Neural control of movement stability: Lessons from studies of neurological patients. Neuroscience 2015, 301, 39–48. [Google Scholar] [CrossRef]
- Latash, M.L. Neurophysiological Basis of Movement; Human Kinetics: Champaign, IL, USA, 2008. [Google Scholar]
- Shunenkov, D.A.; Loginov, A.A.; Bosenko, S.A.; Saveliev, O.G.; Kovaleva, N.Y.; Vorobiev, A.V.; Lebedev, A.S.; Kanarskii, M.M. Present problem of neurororehabilitology: Methods for quantitative assessment of pathological increased muscle tone. MSER 2021, 24, 23–34. [Google Scholar] [CrossRef]
- Pisano, F.; Miscio, G.; Del Conte, C.; Pianca, D.; Candeloro, E.; Colombo, R. Quantitative measures of spasticity in post-stroke patients. Clin. Neurophysiol. 2000, 111, 1015–1022. [Google Scholar] [CrossRef]
- Li, S. Spasticity, Motor Recovery, and Neural Plasticity after Stroke. Front. Neurol. 2017, 8, 120. [Google Scholar] [CrossRef] [PubMed]
- van der Velden, L.L.; de Koff, M.A.C.; Ribbers, G.M.; Selles, R.W. The diagnostic levels of evidence of instrumented devices for measuring viscoelastic joint properties and spasticity; a systematic review. J. Neuroeng. Rehabil. 2022, 19, 16. [Google Scholar] [CrossRef] [PubMed]
- McGibbon, C.A.; Sexton, A.; Jones, M.; O’Connell, C. Elbow spasticity during passive stretch-reflex: Clinical evaluation using a wearable sensor system. J. Neuroeng. Rehabil. 2013, 10, 61. [Google Scholar] [CrossRef] [PubMed]
- Yee, J.; Low, C.Y.; Mohamad Hashim, N.; Che Zakaria, N.A.; Johar, K.; Othman, N.A.; Chieng, H.H.; Hanapiah, F.A. Clinical Spasticity Assessment Assisted by Machine Learning Methods and Rule-Based Decision. Diagnostics 2023, 13, 739. [Google Scholar] [CrossRef]
- Kopecká, B.; Ravnik, D.; Jelen, K.; Bittner, V. Objective Methods of Muscle Tone Diagnosis and Their Application—A Critical Review. Sensors 2023, 23, 7189. [Google Scholar] [CrossRef] [PubMed]
- McGibbon, C.A.; Sexton, A.; Hughes, G.; Wilson, A.; Jones, M.; O’Connell, C.; Parker, K.; Adans-Dester, C.; O’Brien, A.; Bonato, P. Evaluation of a toolkit for standardizing clinical measures of muscle tone. Physiol. Meas. 2018, 39, 085001. [Google Scholar] [CrossRef]
- Amirova, L.E.; Plehuna, A.; Rukavishnikov, I.V.; Saveko, A.A.; Peipsi, A.; Tomilovskaya, E.S. Sharp Changes in Muscle Tone in Humans Under Simulated Microgravity. Front. Physiol. 2021, 12, 661922. [Google Scholar] [CrossRef]
- van den Noort, J.C.; Bar-On, L.; Aertbelien, E.; Bonikowski, M.; Braendvik, S.M.; Brostrom, E.W.; Buizer, A.I.; Burridge, J.H.; van Campenhout, A.; Dan, B.; et al. European consensus on the concepts and measurement of the pathophysiological neuromuscular responses to passive muscle stretch. Eur. J. Neurol. 2017, 24, 981-e38. [Google Scholar] [CrossRef]
- Guo, X.; Wallace, R.; Tan, Y.; Oetomo, D.; Klaic, M.; Crocher, V. Technology-assisted assessment of spasticity: A systematic review. J. NeuroEng. Rehabil. 2022, 19, 138. [Google Scholar] [CrossRef]
- He, J.; Luo, A.; Yu, J.; Qian, C.; Liu, D.; Hou, M.; Ma, Y. Quantitative assessment of spasticity: A narrative review of novel approaches and technologies. Front. Neurol. 2023, 14, 1121323. [Google Scholar] [CrossRef]
- Tricco, A.C.; Lillie, E.; Zarin, W.; O’Brien, K.K.; Colquhoun, H.; Levac, D.; Moher, D.; Peters, M.D.J.; Horsley, T.; Weeks, L.; et al. PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation. Ann. Intern. Med. 2018, 169, 467–473. [Google Scholar] [CrossRef] [PubMed]
- Peters, M.D.J.; Marnie, C.; Tricco, A.C.; Pollock, D.; Munn, Z.; Alexander, L.; McInerney, P.; Godfrey, C.M.; Khalil, H. Updated methodological guidance for the conduct of scoping reviews. JBI Evid. Synth. 2020, 18, 2119–2126. [Google Scholar] [CrossRef] [PubMed]
- Aromataris, E. Furthering the science of evidence synthesis with a mix of methods. JBI Evid. Synth. 2020, 18, 2106–2107. [Google Scholar] [CrossRef] [PubMed]
- Ghotbi, N.; Nakhostin Ansari, N.; Naghdi, S.; Hasson, S. Measurement of lower-limb muscle spasticity: Intrarater reliability of Modified Modified Ashworth Scale. J. Rehabil. Res. Dev. 2011, 48, 83–88. [Google Scholar] [CrossRef]
- Kaya, T.; Karatepe, A.G.; Gunaydin, R.; Koc, A.; Altundal Ercan, U. Inter-rater reliability of the Modified Ashworth Scale and modified Modified Ashworth Scale in assessing poststroke elbow flexor spasticity. Int. J. Rehabil. Res. 2011, 34, 59–64. [Google Scholar] [CrossRef] [PubMed]
- Ansari, N.N.; Naghdi, S.; Mashayekhi, M.; Hasson, S.; Fakhari, Z.; Jalaie, S. Intra-rater reliability of the Modified Modified Ashworth Scale (MMAS) in the assessment of upper-limb muscle spasticity. NeuroRehabilitation 2012, 31, 215–222. [Google Scholar] [CrossRef]
- Beseler, M.R.; Grao, C.M.; Gil, A.; Martinez Lozano, M.D. Walking assessment with instrumented insoles in patients with lower limb spasticity after botulinum toxin infiltration. Neurologia 2012, 27, 519–530. [Google Scholar] [CrossRef]
- Aygun, O.E. Responsiveness of Tonic Stretch Reflex Threshold measured with the Montreal Spasticity Measure. Master’s Thesis, School of Physical and Occupational Therapy McGill University, Montréal, QC, Canada, 2021. [Google Scholar]
- Kim, J.Y.; Park, G.; Lee, S.A.; Nam, Y. Analysis of Machine Learning-Based Assessment for Elbow Spasticity Using Inertial Sensors. Sensors 2020, 20, 1622. [Google Scholar] [CrossRef]
- Ansari, N.N.; Naghdi, S.; Moammeri, H.; Jalaie, S. Ashworth Scales are unreliable for the assessment of muscle spasticity. Physiother. Theory Pract. 2006, 22, 119–125. [Google Scholar] [CrossRef]
- Bohannon, R.W.; Smith, M.B. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys. Ther. 1987, 67, 206–207. [Google Scholar] [CrossRef]
- Kimura, J. Spasticity: Etiology, evaluation, management and the role of botulinum toxin A. Patients Visit Forms and Rating Scales (appendix). Muscle Nerve, 1997; Suppl. 6. [Google Scholar]
- Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef] [PubMed]
- Li, S.; Francisco, G.E.; Zhou, P. Post-stroke Hemiplegic Gait: New Perspective and Insights. Front. Physiol. 2018, 9, 1021. [Google Scholar] [CrossRef] [PubMed]
- Calota, A.; Levin, M.F. Tonic stretch reflex threshold as a measure of spasticity: Implications for clinical practice. Top. Stroke Rehabil. 2009, 16, 177–188. [Google Scholar] [CrossRef] [PubMed]
- Santello, M.; Lang, C.E. Are movement disorders and sensorimotor injuries pathologic synergies? When normal multi-joint movement synergies become pathologic. Front. Hum. Neurosci. 2014, 8, 1050. [Google Scholar] [CrossRef] [PubMed]
- Cenciarini, M.; Loughlin, P.J.; Sparto, P.J.; Redfern, M.S. Stiffness and damping in postural control increase with age. IEEE Trans. Biomed. Eng. 2010, 57, 267–275. [Google Scholar] [CrossRef]
- Damiano, D.L.; Quinlivan, J.; Owen, B.F.; Shaffrey, M.; Abel, M.F. Spasticity versus strength in cerebral palsy: Relationships among involuntary resistance, voluntary torque, and motor function. Eur. J. Neurol. 2001, 8, 40–49. [Google Scholar] [CrossRef] [PubMed]
- O’Dwyer, N.J.; Ada, L.; Neilson, P.D. Spasticity and muscle contracture following stroke. Brain 1996, 119 Pt 5, 1737–1749. [Google Scholar] [CrossRef]
- Basteris, A.; Nijenhuis, S.M.; Stienen, A.H.A.; Buurke, J.H.; Prange, G.B.; Amirabdollahian, F. Training modalities in robot-mediated upper limb rehabilitation in stroke: A framework for classification based on a systematic review. J. NeuroEng. Rehabil. 2014, 11, 111. [Google Scholar] [CrossRef]
- Major, Z.Z.; Vaida, C.; Major, K.A.; Tucan, P.; Brusturean, E.; Gherman, B.; Birlescu, I.; Craciunaș, R.; Ulinici, I.; Simori, G.; et al. Comparative Assessment of Robotic versus Classical Physical Therapy Using Muscle Strength and Ranges of Motion Testing in Neurological Diseases. J. Pers. Med. 2021, 11, 953. [Google Scholar] [CrossRef]
- Yan, G.; Zhang, X.; Liu, Y.; Guo, P.; Liu, Y.; Li, X.; Yong, V.W.; Xue, M. Integrative insights into cerebrometabolic disease: Understanding, management, and future prospects. J. Neurorestoratology 2024, 12, 100107. [Google Scholar] [CrossRef]
- Birulina, Y.G.; Ivanov, V.V.; Buyko, E.E.; Gabitova, I.O.; Kovalev, I.V.; Nosarev, A.V.; Smagliy, L.V.; Gusakova, S.V. Role of H2S in Regulation of Vascular Tone in Metabolic Disorders. Bull. Exp. Biol. Med. 2021, 171, 431–434. [Google Scholar] [CrossRef] [PubMed]
- Amini, B.; Boyle, S.P.; Boutin, R.D.; Lenchik, L. Approaches to Assessment of Muscle Mass and Myosteatosis on Computed Tomography: A Systematic Review. J. Gerontol. A Biol. Sci. Med. Sci. 2019, 74, 1671–1678. [Google Scholar] [CrossRef] [PubMed]
- Garcia-Bernal, M.-I.; Heredia-Rizo, A.M.; Gonzalez-Garcia, P.; Cortés-Vega, M.-D.; Casuso-Holgado, M.J. Validity and reliability of myotonometry for assessing muscle viscoelastic properties in patients with stroke: A systematic review and meta-analysis. Sci. Rep. 2021, 11, 5062. [Google Scholar] [CrossRef] [PubMed]
- Lane, K.; Chandler, E.; Payne, D.; Pomeroy, V.M. Stroke survivors’ recommendations for the visual representation of movement analysis measures: A technical report. Physiotherapy 2020, 107, 36–42. [Google Scholar] [CrossRef] [PubMed]
Database | Search Strategy | Filters |
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Science Direct® | (tone OR stiffness OR spasticity) AND “clinical measures” AND (injury OR lesion) AND adults | 2011–2023 English, French, Portuguese, Spanish |
PubMed® | ((tone OR stiffness OR spasticity) AND (“clinical measures”) AND (injury OR lesion) AND adults)) | 2011–2023 English, French, Portuguese, Spanish |
Web of Science™ | tone AND (stiffness OR spasticity) AND (clinical measures) AND (central nervous system) AND (injury OR lesion) AND adults | 2011–2023 |
Google Scholar® | (tone AND (stiffness OR spasticity) AND (“clinical measures”) AND (“central nervous system”) AND (injury OR lesion) AND adults)) | 2011–2023 English, French, Portuguese, Spanish |
Author/Year | Study Design | Objective | Participants | CNS Disorder |
---|---|---|---|---|
Ghotbi et al., 2011 [28] | Test–retest | To investigate the intra-rater reliability of the MMAS for the assessment of spasticity in the lower limb. | n = 23 (M = 9) Mean age: 37.3 years |
|
Kaya et al., 2011 [29] | Observational | To investigate the inter-rater reliability of the MAS and MMAS for the assessment of poststroke elbow flexor spasticity. | n = 64 (M = 41) (35–82 years) Mean age: 60.5 years |
|
Ansari et al., 2012 [30] | Test–retest | To determine the effect of pain and contracture presence on the reliability of the MAS. | n = 30 (M = 19) (23–80 years) Mean age: 59.0 years |
|
Beseler et al., 2012 [31] | Quasiexperimental | To perform a functional assessment of therapeutic results in patients. | n = 10 (M = 7) (30–69 years) Mean age = 52.9 years |
|
McGibbon et al., 2013 [17] | Experimental | To establish the construct validity of using a wearable sensor system for elbow flexor and extensor spasticity assessments. | n = 9 (M = 5) (28–74 years) |
|
McGibbon et al., 2018 [20] | Observational | To evaluate a new portable toolkit for quantifying upper and lower extremity muscle tone in patients with UMN syndrome. | n = 103 (M = 71) (26–65 years) |
|
Aygun, 2021 [32] | Experimental | To determine the responsiveness of TSRT and the precision of the MSM device. | n = 46 (M = 29) (25–80 years) |
|
Kim et al., 2020 [33] | Experimental | To determine the severity of elbow spasticity by analysing the acceleration and rotation attributes and using machine learning algorithms to classify the degree of spastic movement. | n = 48 (M = 26) Mean age: 61.2 (M); 77.8 (F) years |
|
Author/Year | Clinical Measurement Instruments | Instrument Description | Variable/Concept Under Study | Test Procedures |
---|---|---|---|---|
Ghotbi et al., 2011 [28] |
|
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| Patients were instructed to relax during the test and not to resist the passive movements applied by the PT. The joints were moved with a fast stretching velocity by counting “one-thousand-and-one”. The passive movement was repeated three times for each joint.
(1)
|
(2)
| ||||
(3)
| ||||
Kaya et al., 2011 [29] |
|
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| The unaffected side was used as control to compare the elbow ROM between the two sides. The passive movement was carried out over a duration of 1 s by counting “one-thousand-and-one” and repeated three times.
|
Ansari et al., 2012 [30] |
|
|
| Patients were evaluated on both sides. Each test movement was repeated over 1 s by counting “one-thousand-and-one”. The passive movement was repeated three times for each joint.
(1)
|
Beseler et al., 2012 [31] |
|
|
|
|
McGibbon et al., 2013 [17] |
|
|
|
|
McGibbon et al., 2018 [20] |
|
|
-knee (2) |
|
Aygun, 2021 [32] |
|
|
|
|
Kim et al., 2020 [33] |
|
|
|
|
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Share and Cite
Pinho, L.; Silva, S.; Freitas, M.; Figueira, V.; Pinho, F.; Cunha, C.; Sousa, A.S.P.; Sousa, F.; Silva, A. Clinical Measures for Tone Assessment in Adults with Central Nervous System Disorders—A Scoping Review in a Rehabilitation Context. Appl. Sci. 2024, 14, 8189. https://doi.org/10.3390/app14188189
Pinho L, Silva S, Freitas M, Figueira V, Pinho F, Cunha C, Sousa ASP, Sousa F, Silva A. Clinical Measures for Tone Assessment in Adults with Central Nervous System Disorders—A Scoping Review in a Rehabilitation Context. Applied Sciences. 2024; 14(18):8189. https://doi.org/10.3390/app14188189
Chicago/Turabian StylePinho, Liliana, Sandra Silva, Marta Freitas, Vânia Figueira, Francisco Pinho, Christine Cunha, Andreia S. P. Sousa, Filipa Sousa, and Augusta Silva. 2024. "Clinical Measures for Tone Assessment in Adults with Central Nervous System Disorders—A Scoping Review in a Rehabilitation Context" Applied Sciences 14, no. 18: 8189. https://doi.org/10.3390/app14188189
APA StylePinho, L., Silva, S., Freitas, M., Figueira, V., Pinho, F., Cunha, C., Sousa, A. S. P., Sousa, F., & Silva, A. (2024). Clinical Measures for Tone Assessment in Adults with Central Nervous System Disorders—A Scoping Review in a Rehabilitation Context. Applied Sciences, 14(18), 8189. https://doi.org/10.3390/app14188189