Inertial Gait Sensors to Measure Mobility and Functioning in Hereditary Spastic Paraplegia
A Cross-sectional Multicenter Clinical Study
Abstract
Background and Objectives
Hereditary spastic paraplegia (HSP) causes progressive spasticity and weakness of the lower limbs. As neurologic examination and the clinical Spastic Paraplegia Rating Scale (SPRS) are subject to potential patient-dependent and clinician-dependent bias, instrumented gait analysis bears the potential to objectively quantify impaired gait. The aim of this study was to investigate gait cyclicity parameters by application of a mobile gait analysis system in a cross-sectional cohort of patients with HSP and a longitudinal fast progressing subcohort.
Methods
Using wearable sensors attached to the shoes, patients with HSP and controls performed a 4 × 10 m walking test during regular visits in 3 outpatient centers. Patients were also rated according to the SPRS, and in a subset, questionnaires on quality of life and fear of falling were obtained. An unsupervised segmentation algorithm was used to extract stride parameters and respective coefficients of variation.
Results
Mobile gait analysis was performed in a total of 112 ambulatory patients with HSP and 112 age-matched and sex-matched controls. Although swing time was unchanged compared with controls, there were significant increases in the duration of the total stride phase and the duration of the stance phase, both regarding absolute values and coefficients of variation values. Although stride parameters did not correlate with age, weight, or height of the patients, there were significant associations of absolute stride parameters with single SPRS items reflecting impaired mobility (|r| > 0.50), with patients' quality of life (|r| > 0.44), and notably with disease duration (|r| > 0.27). Sensor-derived coefficients of variation, on the other hand, were associated with patient-reported fear of falling (|r| > 0.41) and cognitive impairment (|r| > 0.40). In a small 1-year follow-up analysis of patients with complicated HSP and fast progression, the absolute values of mobile gait parameters had significantly worsened compared with baseline.
Discussion
The presented wearable sensor system provides parameters of stride characteristics which seem clinically valid to reflect gait impairment in HSP. Owing to the feasibility regarding time, space, and costs, this study forms the basis for larger scale longitudinal and interventional studies in HSP.
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References
1.
Shribman S, Reid E, Crosby AH, Houlden H, Warner TT. Hereditary spastic paraplegia: from diagnosis to emerging therapeutic approaches. Lancet Neurol. 2019;18(12):1136-1146.
2.
Ruano L, Melo C, Silva MC, Coutinho P. The global epidemiology of hereditary ataxia and spastic paraplegia: a systematic review of prevalence studies. Neuroepidemiology. 2014;42(3):174-183.
3.
Schüle R, Wiethoff S, Martus P, et al. Hereditary spastic paraplegia: clinicogenetic lessons from 608 patients. Ann Neurol. 2016;79(4):646-658.
4.
Harding AE. Classification of the hereditary ataxias and paraplegias. Lancet. 1983;1(8334):1151-1155.
5.
Durr A, Brice A, Serdaru M, et al. The phenotype of “pure” autosomal dominant spastic paraplegia. Neurology. 1994;44(7):1274-1274.
6.
McDermott CJ, Burness CE, Kirby J, et al. Clinical features of hereditary spastic paraplegia due to spastin mutation. Neurology. 2006;67(1):45-51.
7.
Piccinini L, Cimolin V, D'Angelo MG, Turconi AC, Crivellini M, Galli M. 3D gait analysis in patients with hereditary spastic paraparesis and spastic diplegia: a kinematic, kinetic and EMG comparison. Eur J Paediatr Neurol. 2011;15(2):138-145.
8.
Wolf SI, Braatz F, Metaxiotis D, et al. Gait analysis may help to distinguish hereditary spastic paraplegia from cerebral palsy. Gait Posture. 2011;33(4):556-561.
9.
Serrao M, Rinaldi M, Ranavolo A, et al. Gait patterns in patients with hereditary spastic paraparesis. PLoS One. 2016;11(10):e0164623.
10.
van Lith BJH, den Boer J, van de Warrenburg BPC, Weerdesteyn V, Geurts AC. Functional effects of botulinum toxin type A in the hip adductors and subsequent stretching in patients with hereditary spastic paraplegia. J Rehabil Med. 2019;51(6):434-441.
11.
Martindale CF, Roth N, Gasner H, Jensen D, Kohl Z, Eskofier BM. Mobile gait analysis using personalised hidden Markov models for hereditary spastic paraplegia patients. Annu Int Conf IEEE Eng Med Biol Soc. 2018;2018:5430-5433.
12.
Martindale CF, Roth N, Ganer H, et al. Technical validation of an automated mobile gait analysis system for hereditary spastic paraplegia patients. IEEE J Biomed Health. 2019;24(5):1490-1499.
13.
Schüle R, Holland-Letz T, Klimpe S, et al. The Spastic Paraplegia Rating Scale (SPRS): a reliable and valid measure of disease severity. Neurology. 2006;67(3):430-434.
14.
Gassner H, Jensen D, Marxreiter F, et al. Gait variability as digital biomarker of disease severity in Huntington's disease. J Neurol. 2020;267(6):1594-1601.
15.
Podsiadlo D, Richardson S. The timed “up & go”: a test of basic functional mobility for frail elderly persons. J Am Geriatr Soc. 1991;39(2):142-148.
16.
Dias N, Kempen GIJM, Todd CJ, et al. The German version of the Falls Efficacy Scale-International Version (FES-I) [in German]. Z Gerontol Geriatr. 2006;39(4):297-300.
17.
Ware JE, Kosinski M, Keller SD. A 12-item short-form health survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34(3):220-233.
18.
Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695-699.
19.
Ullrich M, Hannink J, Gaßner H, Klucken J, Eskofier BM, Kluge F. Unsupervised harmonic frequency-based gait sequence detection for Parkinson's disease. 2019 IEEE EMBS Int Conf Biomed Heal Informatics (BHI). 2019:1-4.
20.
Tesson C, Koht J, Stevanin G. Delving into the complexity of hereditary spastic paraplegias: how unexpected phenotypes and inheritance modes are revolutionizing their nosology. Hum Genet. 2015;134(6):511-538.
21.
Klebe S, Stolze H, Kopper F, et al. Gait analysis of sporadic and hereditary spastic paraplegia. J Neurol. 2004;251(5):571-578.
22.
Cimolin V, Piccinini L, D'Angelo MG, et al. Are patients with hereditary spastic paraplegia different from patients with spastic diplegia during walking? Gait evaluation using 3D gait analysis. Funct Neurol. 2007;22(1):23-28.
23.
Bonnefoy-Mazure A, Turcot K, Kaelin A, Coulon GD, Armand S. Full body gait analysis may improve diagnostic discrimination between hereditary spastic paraplegia and spastic diplegia: a preliminary study. Res Dev Disabil. 2013;34(1):495-504.
24.
Adair B, Rodda J, McGinley JL, Graham HK, Morris ME. Kinematic gait deficits at the trunk and pelvis: characteristic features in children with hereditary spastic paraplegia. Dev Med Child Neurol. 2016;58(8):829-835.
25.
Serrao M, Chini G, Bergantino M, et al. Identification of specific gait patterns in patients with cerebellar ataxia, spastic paraplegia, and Parkinson's disease: a non-hierarchical cluster analysis. Hum Mov Sci. 2018;57:267-279.
26.
Pulido-Valdeolivas I, Gómez-Andrés D, Martín-Gonzalo JA, et al. Gait phenotypes in paediatric hereditary spastic paraplegia revealed by dynamic time warping analysis and random forests. PLoS One. 2018;13(3):e0192345.
27.
van Vugt Y, Stinear J, Davies TC, Zhang Y. Postural stability during gait for adults with hereditary spastic paraparesis. J Biomech. 2019;88:12-17.
28.
Gaßner H, Sanders P, Dietrich A, et al. Clinical relevance of standardized mobile gait tests. Reliability analysis between gait recordings at hospital and home in Parkinson's disease: a pilot study. J Parkinsons Dis. 2020;10(4):1763-1773.
29.
Gaßner H, List J, Martindale CF, et al. Functional gait measures correlate to fear of falling, and quality of life in patients with Hereditary Spastic Paraplegia: a cross-sectional study. Clin Neurol Neurosurg. 2021;209:106888.
30.
Klimpe S, Schüle R, Kassubek J, et al. Disease severity affects quality of life of hereditary spastic paraplegia patients. Eur J Neurol. 2011;19(1):168-171.
31.
Braschinsky M, Rannikmäe K, Krikmann Ü, et al. Health-related quality of life in patients with hereditary spastic paraplegia in Estonia. Spinal Cord. 2011;49(2):175-181.
32.
Kerstens HCJW, Satink T, Nijkrake MJ, et al. Stumbling, struggling, and shame due to spasticity: a qualitative study of adult persons with hereditary spastic paraplegia. Disabil Rehabil. 2019;42(26):1-8.
33.
van Lith BJH, Kerstens HCJW, van den Bemd LAC, et al. Experienced complaints, activity limitations and loss of motor capacities in patients with pure hereditary spastic paraplegia: a web-based survey in the Netherlands. Orphanet J Rare Dis. 2020;15(1):64.
34.
Bertolucci F, Martino SD, Orsucci D, et al. Robotic gait training improves motor skills and quality of life in hereditary spastic paraplegia. Neurorehabilitation. 2015;36(1):93-99.
35.
Servelhere KR, Faber I, Martinez A, et al. Botulinum toxin for hereditary spastic paraplegia: effects on motor and non-motor manifestations. Arq Neuropsiquiatr. 2018;76(3):183-188.
36.
de Lima FD, Faber I, Servelhere KR, et al. Randomized trial of botulinum toxin type A in hereditary spastic paraplegia—the SPASTOX trial. Mov Disord. 2021;36(7):1654-1663.
37.
Rattay TW, Boldt A, Völker M, et al. Non-motor symptoms are relevant and possibly treatable in hereditary spastic paraplegia type 4 (SPG4). J Neurol. 2019;267(2):369-379.
38.
Jacinto-Scudeiro LA, Machado GD, Ayres A, et al. Are cognitive changes in hereditary spastic paraplegias restricted to complicated forms? Front Neurol. 2019;10:508.
39.
Springer S, Giladi N, Peretz C, Yogev G, Simon ES, Hausdorff JM. Dual‐tasking effects on gait variability: the role of aging, falls, and executive function. Mov Disord. 2006;21(7):950-957.
40.
Hausdorff JM, Schweiger A, Herman T, Yogev-Seligmann G, Giladi N. Dual-task decrements in gait: contributing factors among healthy older adults. J Gerontol Ser. 2008;63(12):1335-1343.
41.
Holtzer R, Wang C, Verghese J. The relationship between attention and gait in aging: facts and fallacies. Motor Control. 2012;16(1):64-80.
42.
Ibrahim AA, Küderle A, Gaßner H, Klucken J, Eskofier BM, Kluge F. Inertial sensor-based gait parameters reflect patient-reported fatigue in multiple sclerosis. J Neuroeng Rehabil. 2020;17(1):165.
Information & Authors
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© 2022 American Academy of Neurology.
Publication History
Received: January 17, 2022
Accepted: April 19, 2022
Published online: June 6, 2022
Published in issue: September 6, 2022
Disclosure
M.O. reports—outside of the submitted work—part-time employment by Portabiles HealthCare Technologies GmbH which develops and marketizes the Mobile GaitLab system. B.E. holds a patent on human gait assessment and reports shares of Portabiles Healthcare Technologies GmbH. J.K. holds a patent on human gait assessment and reports shares of Portabiles Healthcare Technologies GmbH. J.W. holds a patent on human gait assessment (without holding shares). The other authors report no disclosures relevant to the manuscript. Go to Neurology.org/N for full disclosures.
Study Funding
This work was supported by the German Bundesministerium für Bildung und Forschung (BMBF) through the TreatHSP consortium (01GM1905B to M.R., J.W., and H.G., 01GM1905A to R.S., 01GM1905C to S.K.), by the Deutsche Forschungsgemeinschaft (German Research Foundation; 270949263/GRK2162 to M.R. and J.W.; Heisenberg professorship program grant 526 number ES 434/8-1 to B.E.), by the European Union's Horizon 2020 research and innovation program under the frame of the EJP-RD network PROSPAX (No 441409627 to R.S.), by the German Network of Neurodegenerative Disorders (DZNE), by the “Förderverein für HSP-Forschung,” and by the “Forschungsstiftung Medizin” at the University Hospital Erlangen. M.R. is a fellow of the Clinician Scientist Programme (IZKF, University Hospital Erlangen). R.S. is a member of the European Reference Network for Rare Neurological Diseases (ERN-RND). H.G. was supported by the Fraunhofer Internal Programs under Grant Nos. Attract 044-602140 and 044-602150.
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