Background Cerebellar damage can often result in disabilities affecting the peripheral regions of the body. These include poor and inaccurate coordination, tremors and irregular movements that often manifest as disorders associated with balance, gait and speech. The severity assessment of Cerebellar ataxia (CA) is determined by expert opinion and is likely to be subjective in nature. This paper investigates automated versions of three commonly used tests: Finger to Nose test (FNT), test for upper limb Dysdiadochokinesia Test (DDK) and Heel to Shin Test (HST), in evaluating disability due to CA. Methods Limb movements associated with these tests are measured using Inertial Measurement Units (IMU) to capture the disability. Kinematic parameters such as acceleration, velocity and angle are considered in both time and frequency domain in three orthogonal axes to obtain relevant disability related information. The collective dominance in the data distributions of the underlying features were observed though the Principal Component Analysis (PCA). The dominant features were combined to substantiate the correlation with the expert clinical assessments through Linear Discriminant Analysis. Here, the Pearson correlation is used to examine the relationship between the objective assessments and the expert clinical scores while the performance was also verified by means of cross validation. Results The experimental results show that acceleration is a major feature in DDK and HST, whereas rotation is the main feature responsible for classification in FNT. Combining the features enhanced the correlations in each domain. The subject data was classified based on the severity information based on expert clinical scores. Conclusion For the predominantly translational movement in the upper limb FNT, the rotation captures disability and for the DDK test with predominantly rotational movements, the linear acceleration captures the disability but cannot be extended to the lower limb HST. The orthogonal direction manifestation of ataxia attributed to sensory measurements was determined for each test. Trial registration Human Research and Ethics Committee, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia (HREC Reference Number: 11/994H/16). Electronic supplementary material The online version of this article (10.1186/s12984-019-0490-3) contains supplementary material, which is available to authorized users.

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Neurological disorders typically exhibit movement disabilities and disorders such as cerebellar ataxia (CA) can cause coordination inaccuracies often manifested as disabilities associated with gait, balance and speech. Since the severity assessment of the disorder is based on the expert clinical opinion, it is likely to be subjective. Automated versions of two upper limb tests: Finger to Nose test (FNT) and Diadochokinesia (DDK) test are investigated in this paper. Inertial Measurement Units (IMU) (BioKin TM) are employed to capture the disability by measuring limb movements. Translational and rotational accelerations considered as kinematic parameters provided the features relevant to characteristic movements intrinsic to the disability. Principal Component Analysis (PCA) and multi-class Linear Discriminant classifier (LDA) were instrumental in dominant features correlating with the clinical scores. The relationship between clinicians assessment and the objective analysis is examined using Pearson Correlation. This study found that although FNT predominantly consist of translational movements, rotation was the dominant feature while for the case of DDK that predominantly consist of rotational movements, acceleration was the dominant feature. The degree of correlation in each test was also enhanced by combining the features in different tests.

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