Uncovering Subtle Gait Deterioration in People with Early-Stage Multiple Sclerosis Using Inertial Sensors: A 2-Year Multicenter Longitudinal Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Participants
2.2. Procedures
2.3. Outcome and Outcome Measures
2.3.1. Disability
2.3.2. Walking Endurance
2.3.3. Fatigue
2.3.4. Instrumented Walking Parameters
- Cadence (stride/min): computed as 60/Tstride, where Tstride is the stride duration (i.e., the time interval between two consecutive heel-strikes of the same foot, estimated following Salarian et al. [23]).
- Stride regularity (unitless): quantified using the method proposed by Moe-Nilssen & Helbostad [24]. In particular, the normalized autocorrelation function was computed from the trunk acceleration modulus. The first and second peak values of this function, corresponding, respectively, to a time lag equal to step and stride duration, were used to quantify the regularity of consecutive steps and strides (see Angelini et al. [25]). Increasing values, from 0 to 1, indicate higher step and stride regularity. In this study, stride regularity was preferred to step regularity since the latter has been often used as a measure of gait symmetry (see [26,27]).
- Gait instability (unitless): quantified by the short term Lyapunov exponent (sLyE) computed from the lower back antero-posterior (AP) and medio-lateral (ML) accelerations, as detailed by Caronni et al. [13]. Given that sLyE is affected by data length [28,29,30], each 10-stride steady state walking bout was re-sampled to 1000 frames (10 strides × 100 frames) to maintain equal data length across walking bouts and participants. Hence, sLyE was computed on each time-normalized walking bout and then averaged over the whole test, as proposed by Sloot et al. [31]. Larger values of sLyE mean decreased local dynamic stability, that is decreased ability of the balance control system to deal with small perturbations typically occurring during locomotion, such as internal control errors or external disturbances [28,32].
- Gait symmetry (%): quantified by the improved Harmonic Ratio (iHR) calculated from trunk AP and ML accelerations [15,18]. In summary, we used a fast discrete Fourier transform to decompose acceleration signals into harmonics. Hence, iHR was computed as the percentage ratio between the sum of the powers of the first 10 in-phase harmonics to the sum of the powers of the first 20 (in-phase and out-of-phase) harmonics. A range from 0 (no symmetry) to 100% (perfect symmetry) was used to describe gait symmetry (see Pasciuto et al. [33]).
2.3.5. Perceived Walking Ability
2.4. Statistical Analysis
3. Results
3.1. Clinical Assessment
3.2. Instrumented Walking Assessment
3.3. Instrumented Gait Variables and EDSS
3.4. Instrumented Gait Variables and Perceived Assessment of Gait
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Variable | Baseline (n = 56) | 2-Year Follow Up (n = 56) | 2-Year Follow Up Deteriorated Group (n = 17) | 2-Year Follow Up Non-Deteriorated Group (n = 39) |
---|---|---|---|---|
Age (years) | 38.2 ± 10.7 | 40.0 ± 11.0 | 44.6 ± 9.8 | 38.4 ± 10.8 |
Female (n, %) | 35, 63% | 35, 63% | 10, 59% | 26, 67% |
EDSS (points) | 1.5 ± 0.7 | 1.8 ± 1.0 | 2.7 ± 0.8 | 1.4 ± 0.7 |
Years since diagnosis | 2.2 ± 1.8 | 4.2 ± 1.9 | 4.1 ± 1.5 | 4.2 ± 2.1 |
6MWT (m) | 564.0 ± 78.7 | 574.8 ± 87.6 | 554.5 ± 108.1 | 585.5 ± 76.9 |
MSWS-12 (points) | 31.3 ± 14.1 | 31.4 ± 14.2 | 38.9 ± 17.0 | 28.8 ± 12.3 |
FSS (points) | 3.1 ± 1.7 | 3.2 ± 1.8 | 3.7 ± 1.8 | 3.0 ± 1.8 |
Variable | Baseline (n = 56) | 2-Year Follow Up (n = 56) | 2-Year Follow Up Deteriorated Group (n = 17) | 2-Year Follow Up Non-Deteriorated Group (n = 39) |
---|---|---|---|---|
Cadence (stride/min) | 63.4 ± 4.5 | 64.2 ± 5.6 | 63.8 ± 7.7 | 64.7 ± 4.8 |
Stride Regularity (a.u.) | 0.9 ± 0.1 | 0.9 ± 0.1 | 0.9 ± 0.1 | 0.9 ± 0.1 |
Gait Symmetry AP (a.u.) | 82.0 ± 6.3 | 84.2 ± 5.7 | 82.7 ± 7.0 | 84.8 ± 5.0 |
Gait Symmetry ML (a.u.) | 80.2 ± 10.4 | 83.1 ± 8.9 | 80.5 ± 11.7 | 84.1 ± 7.2 |
Gait Instability AP (a.u.) | 0.7 ± 0.1 | 0.7 ± 0.1 | 0.8 ± 0.1 | 0.7 ± 0.1 |
Gait Instability ML (a.u.) | 0.7 ± 0.1 | 0.8 ± 0.1 | 0.8 ± 0.1 | 0.7 ± 0.1 |
Instrumented Variable | EDSS (n = 17) | MSWS-12 (n = 17) |
---|---|---|
Cadence | −0.35 | 0.17 |
Stride regularity | −0.49 * | −0.24 |
Gait instability AP | 0.36 | 0.73 * |
Gait instability ML | 0.52 * | 0.20 |
Gait symmetry AP | −0.45 | −0.09 |
Gait symmetry ML | −0.55 * | −0.07 |
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Gervasoni, E.; Anastasi, D.; Di Giovanni, R.; Solaro, C.; Rovaris, M.; Brichetto, G.; Confalonieri, P.; Tacchino, A.; Carpinella, I.; Cattaneo, D. Uncovering Subtle Gait Deterioration in People with Early-Stage Multiple Sclerosis Using Inertial Sensors: A 2-Year Multicenter Longitudinal Study. Sensors 2023, 23, 9249. https://doi.org/10.3390/s23229249
Gervasoni E, Anastasi D, Di Giovanni R, Solaro C, Rovaris M, Brichetto G, Confalonieri P, Tacchino A, Carpinella I, Cattaneo D. Uncovering Subtle Gait Deterioration in People with Early-Stage Multiple Sclerosis Using Inertial Sensors: A 2-Year Multicenter Longitudinal Study. Sensors. 2023; 23(22):9249. https://doi.org/10.3390/s23229249
Chicago/Turabian StyleGervasoni, Elisa, Denise Anastasi, Rachele Di Giovanni, Claudio Solaro, Marco Rovaris, Giampaolo Brichetto, Paolo Confalonieri, Andrea Tacchino, Ilaria Carpinella, and Davide Cattaneo. 2023. "Uncovering Subtle Gait Deterioration in People with Early-Stage Multiple Sclerosis Using Inertial Sensors: A 2-Year Multicenter Longitudinal Study" Sensors 23, no. 22: 9249. https://doi.org/10.3390/s23229249
APA StyleGervasoni, E., Anastasi, D., Di Giovanni, R., Solaro, C., Rovaris, M., Brichetto, G., Confalonieri, P., Tacchino, A., Carpinella, I., & Cattaneo, D. (2023). Uncovering Subtle Gait Deterioration in People with Early-Stage Multiple Sclerosis Using Inertial Sensors: A 2-Year Multicenter Longitudinal Study. Sensors, 23(22), 9249. https://doi.org/10.3390/s23229249