Clinical assessment of gait in individuals with multiple sclerosis using wearable inertial sensors: Comparison with patient-based measure

Abstract Aim The main purpose of the present study was to verify the feasibility of wearable inertial sensors (IMUs) in a clinical setting to screen gait and functional mobility in Italian older persons. In particular, we intended to verify the capability of IMUs to discriminate individuals with and without cognitive impairments and assess the existence of significant correlations between mobility parameters extracted by processing trunk accelerations and cognitive status. Methods This is a cross-sectional study performed on 213 adults aged over 65 years (mean age 77.0 ± 5.4; 62% female) who underwent cognitive assessment (through Addenbrooke’s Cognitive Examination Revised, ACE-R) instrumental gait analysis and the Timed Up and Go (TUG) test carried out using a wearable IMU located in the lower back. Results Individuals with cognitive impairments exhibit a peculiar gait pattern, characterized by significant reduction of speed (− 34% vs. healthy individuals), stride length (− 28%), cadence (− 9%), and increase in double support duration (+ 11%). Slight, but significant changes in stance and swing phase duration were also detected. Poorer performances in presence of cognitive impairment were observed in terms of functional mobility as overall and sub-phase TUG times resulted significantly higher with respect to healthy individuals (overall time, + 38%, sub-phases times ranging from + 22 to + 34%), although with some difference associated with age. The severity of mobility alterations was found moderately to strongly correlated with the ACE-R score (Spearman’s rho = 0.58 vs. gait speed, 0.54 vs. stride length, 0.66 vs. overall TUG time). Conclusion The findings obtained in the present study suggest that wearable IMUs appear to be an effective solution for the clinical assessment of mobility parameters of older persons screened for cognitive impairments within a clinical setting. They may represent a useful tool for the clinician in verifying the effectiveness of interventions to alleviate the impact of mobility limitations on daily life in cognitively impaired individuals.

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Using wearable inertial sensors to detect different strategies for the sit-to-stand transition in multiple sclerosis

European Conference on Cognitive Ergonomics 2021 ◽

10.1145/3452853.3452862 ◽

2021 ◽

Author(s):

Aiswarya Nagasubramony ◽

Rebecca F Player ◽

Carina E I Westling ◽

Kathleen Galvin ◽

Harry J. Witchel

Keyword(s):

Multiple Sclerosis ◽

Inertial Sensors ◽

Sit To Stand ◽

Wearable Inertial Sensors

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Wearable inertial sensors are highly sensitive in the detection of gait disturbances and fatigue at early stages of multiple sclerosis

BMC Neurology ◽

10.1186/s12883-021-02361-y ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Roy Müller ◽

Daniel Hamacher ◽

Sascha Hansen ◽

Patrick Oschmann ◽

Philipp M. Keune

Keyword(s):

Multiple Sclerosis ◽

Inertial Sensors ◽

Linear Trend ◽

Significant Linear Trend ◽

Subjective Fatigue ◽

Gait Parameters ◽

Highly Sensitive ◽

Wearable Inertial Sensors ◽

Gait Disturbances ◽

Healthy Participants

Abstract Background The aim of the current study was to examine multiple gait parameters obtained by wearable inertial sensors and their sensitivity to clinical status in early multiple sclerosis (MS). Further, a potential correlation between gait parameters and subjective fatigue was explored. Methods Automated gait analyses were carried out on 88 MS patients and 31 healthy participants. To measure gait parameters (i.e. walking speed, stride length, stride duration, duration of stance and swing phase, minimal toe-to-floor distance), wearable inertial sensors were utilized throughout a 6-min 25-ft walk. Additionally, self-reported subjective fatigue was assessed. Results Mean gait parameters consistently revealed significant differences between healthy participants and MS patients from as early as an Expanded Disability Status Scale (EDSS) value of 1.5 onwards. Further, MS patients showed a significant linear trend in all parameters, reflecting continuously deteriorating gait performance throughout the test. This linear deterioration trend showed significant correlations with fatigue. Conclusions Wearable inertial sensors are highly sensitive in the detection of gait disturbances, even in early MS, where global scales such as the EDSS do not provide any clinical information about deviations in gait behavior. Moreover, these measures provide a linear trend parameter of gait deterioration that may serve as a surrogate marker of fatigue. In sum, these results suggest that classic timed walking tests in routine clinical practice should be replaced by readily and automatically applicable gait assessments, as provided by inertial sensors.

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