Objective: To detect the morning akinesia (MA) through the analysis of the gait fluidity (GF) measured by the sensor STAT-ON.

Background: The STAT-ON sensor’s detection of ON-OFF motor state is based mostly on the GF, which is a continuous variable obtained with this sensor and that characterizes the Parkinsonian gait [1,2].

Method: Retrospective analysis from two PD outpatient clinic databases. We selected PD patients who had worn the STAT-ON and were specifically asked about the presence of MA. PD patients were divided into group 0 (MA is not present and not clinically suspected), group 1 (MA is not well-reported by the patient but is suspected by the clinician), group 2 (MA is present and the patient knows the time-to-ON after the morning levodopa dose). Days with more than 8 hours of monitoring were included in the analysis after a 7-day monitoring period per patient. Temporal aggregation of the GF per minute of each patient in the first hour of monitoring was performed and the mean GF measurements of this first hour were calculated and compared with the mean GF of the rest of the day. The mean of means and the lowest mean of the GF were the two parameters chosen for the comparison between the first morning hour versus the rest of the day (the lowest measurement of the means represents the greatest bradykinesia). The analysis was done in the three groups using a paired Student t test.

Results: Twenty-eight PD patients were included (67,75 ± 8,21 years old, 60.7% males, mean PD duration 8,39 ± 6,07 years, mean UPDRS-III ON 17,93 ± 7,34, mean levodopa dosage 477,68 ± 208,45 mg, mean levodopa equivalent dosage 786,94 ± 417,43 mg). The lowest mean and the mean of means of the GF was -0.28 (p=0,46) and 0.33 (p=0,36) in group 0 and  -0.45 (P=0,26) and -0.25 (P=0,4) in group 1 respectively. We found statistically significant differences in group 2 with the lowest mean of -1.1 (p<0.05) and a mean of means of -0.5 (p<0.05) [table 1].

Conclusion: The morning akinesia can be detected by the STAT-ON sensor through the analysis of GF. These preliminary results need further replication in future studies with larger samples.

References: [1] Rodríguez-Molinero A, Samà A, Pérez-López C, et al. Analysis of correlation between an accelerometer-Based algorithm for Detecting Parkinsonian gait and UPDRS subscales. Front Neurol. 2017;8(SEP). doi:10.3389/fneur.2017.00431
[2] Samà A, Pérez-López C, Rodríguez-Martín D, et al. Estimating bradykinesia severity in Parkinson’s disease by analysing gait through a waist-worn sensor. Comput Biol Med. 2017;84:114-123. doi:10.1016/j.compbiomed.2017.03.020

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MDS Abstracts - https://www.mdsabstracts.org/abstract/exploring-the-morning-akinesia-in-parkinsons-disease-with-the-wearable-sensor-stat-on/