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BackgroundHSP is characterised by spasticity and progressive gait impairment. There’s no reliable way to monitor gait deterioration during clinics. Optoelectronic systems have demonstrated differing characteristics between gait of HSP patients and controls. They’re expensive and impractical for use in clinic settings. Inertial sensors haven’t been used to characterise HSP gaitObjectivesStudy use of inertial sensors to identify gait characteristics that differentiate mild HSP patients from controls. To identify a gait based biomarker which can be used to monitor disease progression in a longitudinal study.MethodsNeurological examination, SPRS, Modified Ashworth score, brief pain inventory were undertaken. Instrumented timed up and go (iTUG) and instrumented 10 metre walk tests (i10) wearing an inertial sensor during clinic appointments at 6 month intervals.ResultsGait variables differentiating between patients and controls, including those with mild disease, were identified. Parameters differentiating between patients with SPG4 and SPG7 mutations were found. 8 patients were re-assessed after 6 months. Analysis did not show gait deterioration.ConclusionInertial sensors can detect differences between HSP patients and controls, including those mildly affected. They can also differentiate between patients with different mutations. Further follow up data is needed to assess whether inertial sensors can predict future gait deterioration.

AimTo identify clinical, radiological and instrumented gait correlates predictive of natural history in a cohort of HSP patients.BackgroundHSP is a rare heterogeneous group of neurodegenerative disorders. We present our experi- ence managing a large cohort of HSP patients in the regional centre for HSP. We believe Sheffield Teaching Hospitals to have the largest cohort in the North of England.Methodology and ResultsOur cohort comprises 426 patients, 246 male (57.7%) of which 290 were geneti- cally characterized. The commonest mutation is in SPASTIN (SPG4, 38.3%), whilst REEP1 (SPG31) and SPG11 mutations make up 3.1% and 2.1% respectively. Sheffield also holds the largest cohort of SPG7 patients in the UK (n=54) accounting for 18.6% of genetic HSP. The remainder have mutations in KIF5A, Atlastin, WASHC5, KIAA0196, NIPA1, ARSACS, CYP27A1, CYP7B1, AP4S1, GBA2 and L1CAM. Over 240 patients have had detailed MR imaging which has identified novel features in HSP. Repeated instrumented gait monitoring and cognitive assessments have shown novel clinical markers suggesting disease progression.ConclusionFor rare disorders like HSP, specialised clinics optimise comprehensive longitudinal clinical and radiological data collection for large cohorts. This develops local expertise and helps identify novel radiological and clinically relevant biomarkers, enabling better patient care.klprice1@sheffield.ac.uk