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IMU Insole-Derived Gait Digital Biomarkers in idiopathic RBD and Parkinson Disease

JH. Jung, M. Son, J. Jeon, SY. Kang, PH. Lee, SJ. Kim (Busan, Republic of Korea)

Meeting: 2026 International Congress

Keywords: Parkinson’s

Category: Parkinson's disease: Biomarkers (non-Neuroimaging)

Objective: To identify IMU insole-derived gait biomarkers differentiating healthy controls (HC), idiopathic rapid eye movement sleep behavior disorder (iRBD), and Parkinson disease (PD) during a 10-meter walk test.

Background: Gait in PD is characterized by slowing, shorter strides, reduced ankle motion, and increased irregularity. IMU-embedded insoles can capture spatiotemporal and nonlinear gait features without laboratory infrastructure and may provide digital biomarkers in iRBD, a prodromal stage of PD.

Method: We analyzed 301 participants: HC (n=102), iRBD (n=46), mild PD (Hoehn and Yahr 1–2, n=102), and moderate PD (Hoehn and Yahr 2.5–3, n=51). Participants performed a 10-meter walk at slow, preferred, and fast speeds while wearing 6-axis IMU insoles. Features included gait speed, normalized stride length, walking dynamic index, double support time, swing asymmetry, ankle dorsiflexion–plantarflexion range of motion (ROM), estimated anterior-posterior center-of-gravity velocity, and early-stance sample entropy. Mixed-design analysis of variance was applied to 1,587 features with false discovery rate correction.

Results: Ankle ROM showed the largest group effect (left partial eta-squared=0.278; right partial eta-squared=0.260; both false discovery rate-corrected p<0.001), with a monotonic decline across stages. Early-stance sample entropy also differed (partial eta-squared=0.164, p<0.001), increasing from 0.79±0.22 in HC to 1.10±0.30 in moderate PD. Normalized stride length (partial eta-squared=0.152), walking dynamic index (partial eta-squared=0.140), gait speed (partial eta-squared=0.128), and anterior-posterior center-of-gravity velocity (partial eta-squared=0.119) decreased progressively, whereas double support time (partial eta-squared=0.067) and swing asymmetry (partial eta-squared=0.062) increased. Faster walking amplified inter-group differences.

Conclusion: Reduced ankle ROM and increased gait entropy capture complementary aspects of gait dysfunction—kinematic rigidity and movement irregularity—in iRBD and PD. IMU insole-derived metrics may serve as wearable digital biomarkers for prodromal detection and disease severity monitoring.

Table 1. Key IMU Gait Features by Group

Table 1. Key IMU Gait Features by Group

References: 1. Maetzler W, et al. Quantitative wearable sensors for objective assessment of Parkinson’s disease. Mov Disord. 2013;28(12):1628–37.
2. Del Din S, et al. Free-living monitoring of Parkinson’s disease: lessons from the field. Mov Disord. 2016;31(9):1293–313.
3. Kluge F, et al. Sensor-based gait analysis as a digital biomarker for Parkinson’s disease severity. npj Digit Med. 2021;4(1):126.

To cite this abstract in AMA style:

JH. Jung, M. Son, J. Jeon, SY. Kang, PH. Lee, SJ. Kim. IMU Insole-Derived Gait Digital Biomarkers in idiopathic RBD and Parkinson Disease [abstract]. Mov Disord. 2026; 41 (suppl 1). https://www.mdsabstracts.org/abstract/imu-insole-derived-gait-digital-biomarkers-in-idiopathic-rbd-and-parkinson-disease/. Accessed October 1, 2026.
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