Limits...
A new instrumented method for the evaluation of gait initiation and step climbing based on inertial sensors: a pilot application in Parkinson's disease.

Bonora G, Carpinella I, Cattaneo D, Chiari L, Ferrarin M - J Neuroeng Rehabil (2015)

Bottom Line: Significant correlation was found for the validation group between temporal parameters extracted from wearable sensors and force platforms and between medio-lateral component of trunk acceleration and correspondent COP displacement.Validity of the method was confirmed by the significant correlation between parameters extracted from wearable sensors and force platforms.This method could be a possible valid instrument for a better understanding of feed-forward anticipatory strategies.

View Article: PubMed Central - PubMed

Affiliation: Biomedical Technology Department, Found. Don C. Gnocchi Onlus, IRCCS, Via Capecelatro 66, 20148, Milan, Italy. gbonora@dongnocchi.it.

ABSTRACT

Background: Step climbing is a demanding task required for personal autonomy in daily living. Anticipatory Postural Adjustments (APAs) preceding gait initiation have been widely investigated revealing to be hypometric in Parkinson's disease (PD) with consequences in movement initiation. However, only few studies focused on APAs prior to step climbing. In this work, a novel method based on wearable inertial sensors for the analysis of APAs preceding gait initiation and step climbing was developed to further understand dynamic balance control. Validity and sensitivity of the method have been evaluated.

Methods: Eleven PD and 20 healthy subjects were asked to perform two transitional tasks from quiet standing to level walking, and to step climbing respectively. All the participants wore two inertial sensors, placed on the trunk (L2-L4) and laterally on the shank. In addition, a validation group composed of healthy subjects and 5 PD patients performed the tasks on two force platforms. Correlation between parameters from wearable sensors and force platforms was evaluated. Temporal parameters and trunk acceleration from PD and healthy subjects were analyzed.

Results: Significant correlation was found for the validation group between temporal parameters extracted from wearable sensors and force platforms and between medio-lateral component of trunk acceleration and correspondent COP displacement. These results support the validity of the method for evaluating APAs prior to both gait initiation and step climbing. Comparison between PD subjects and a subgroup of healthy controls confirms a reduction in PD of the medio-lateral acceleration of the trunk during the imbalance phase in the gait initiation task and shows similar trends during the imbalance and unloading phase of the step climbing task. Interestingly, PD subjects presented difficulties in adapting the medio-lateral amplitude of the imbalance phase to the specific task needs.

Conclusions: Validity of the method was confirmed by the significant correlation between parameters extracted from wearable sensors and force platforms. Sensitivity was proved by the capability to discriminate PD subjects from healthy controls. Our findings support the applicability of the method to subjects of different age. This method could be a possible valid instrument for a better understanding of feed-forward anticipatory strategies.

No MeSH data available.


Related in: MedlinePlus

Angular velocity of the shank respect to its medio-lateral axis: the first peak of the signal (Ωpk) is reported while red dots correspond to heel-off, toe-off and foot contact of the leading limb as recognized by the proposed detection algorithm.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4419387&req=5

Fig3: Angular velocity of the shank respect to its medio-lateral axis: the first peak of the signal (Ωpk) is reported while red dots correspond to heel-off, toe-off and foot contact of the leading limb as recognized by the proposed detection algorithm.

Mentions: Temporal instants were then extracted from the wearable inertial system data. The acceleration signals recorded at trunk level were transformed to horizontal-vertical coordinate system [35] and filtered using a fourth order, zero-phase, low-pass Butterworth filter with a cut-off frequency of 3.5 Hz, as proposed by Mancini et al. [19]. The same filter was also applied to angular velocity data recorded by the sensor placed on the shank. The APA onset was detected with a threshold-based algorithm applied to the ML acceleration of the trunk sensor [19] with the threshold set as the SD of the signal during the quiet standing period preceding task initiation, multiplied by a factor A. The shank angular velocity around the ML axis was used to identify heel-off and toe-off instants, as shown in Figure 3. In particular, the first peak of the signal (Ωpk) was detected, then the heel-off was estimated as the first instant, following the APA onset, at which the angular velocity became higher than Ωpk value multiplied by a factor H. Toe-off was identified as the first instant, following the peak, at which the signal became lower than Ωpk multiplied by a factor T. The initial calibration of the thresholds was performed considering the data collected on VG subjects, tested in the motion lab with both force plate and inertial sensors. During the calibration procedure, different sets of temporal instants were computed by varying the multiplicative parameters A, H and T. In particular, factor A was varied between values 1 and 5 with unitary incremental steps, while H and T were varied between 0 and 1 with incremental steps equal to 0.01 and 0.05 respectively. For each set of instants and for each subject, the mean absolute errors (MAEs) between instants calculated from force plates data and frames extracted from inertial sensors signals were computed and averaged among all subjects. The final values of A, H and T were then chosen as those which minimized the averaged errors. Finally, the foot contact instant was estimated as the median point between the second peak of the angular velocity and the preceding zero-crossing event; the point was chosen as the one that minimize MAEs. The set of extracted thresholds was then applied to all subjects, including the PD patients tested in the rehabilitation gym, without any further usage of the force plate.Figure 3


A new instrumented method for the evaluation of gait initiation and step climbing based on inertial sensors: a pilot application in Parkinson's disease.

Bonora G, Carpinella I, Cattaneo D, Chiari L, Ferrarin M - J Neuroeng Rehabil (2015)

Angular velocity of the shank respect to its medio-lateral axis: the first peak of the signal (Ωpk) is reported while red dots correspond to heel-off, toe-off and foot contact of the leading limb as recognized by the proposed detection algorithm.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4419387&req=5

Fig3: Angular velocity of the shank respect to its medio-lateral axis: the first peak of the signal (Ωpk) is reported while red dots correspond to heel-off, toe-off and foot contact of the leading limb as recognized by the proposed detection algorithm.
Mentions: Temporal instants were then extracted from the wearable inertial system data. The acceleration signals recorded at trunk level were transformed to horizontal-vertical coordinate system [35] and filtered using a fourth order, zero-phase, low-pass Butterworth filter with a cut-off frequency of 3.5 Hz, as proposed by Mancini et al. [19]. The same filter was also applied to angular velocity data recorded by the sensor placed on the shank. The APA onset was detected with a threshold-based algorithm applied to the ML acceleration of the trunk sensor [19] with the threshold set as the SD of the signal during the quiet standing period preceding task initiation, multiplied by a factor A. The shank angular velocity around the ML axis was used to identify heel-off and toe-off instants, as shown in Figure 3. In particular, the first peak of the signal (Ωpk) was detected, then the heel-off was estimated as the first instant, following the APA onset, at which the angular velocity became higher than Ωpk value multiplied by a factor H. Toe-off was identified as the first instant, following the peak, at which the signal became lower than Ωpk multiplied by a factor T. The initial calibration of the thresholds was performed considering the data collected on VG subjects, tested in the motion lab with both force plate and inertial sensors. During the calibration procedure, different sets of temporal instants were computed by varying the multiplicative parameters A, H and T. In particular, factor A was varied between values 1 and 5 with unitary incremental steps, while H and T were varied between 0 and 1 with incremental steps equal to 0.01 and 0.05 respectively. For each set of instants and for each subject, the mean absolute errors (MAEs) between instants calculated from force plates data and frames extracted from inertial sensors signals were computed and averaged among all subjects. The final values of A, H and T were then chosen as those which minimized the averaged errors. Finally, the foot contact instant was estimated as the median point between the second peak of the angular velocity and the preceding zero-crossing event; the point was chosen as the one that minimize MAEs. The set of extracted thresholds was then applied to all subjects, including the PD patients tested in the rehabilitation gym, without any further usage of the force plate.Figure 3

Bottom Line: Significant correlation was found for the validation group between temporal parameters extracted from wearable sensors and force platforms and between medio-lateral component of trunk acceleration and correspondent COP displacement.Validity of the method was confirmed by the significant correlation between parameters extracted from wearable sensors and force platforms.This method could be a possible valid instrument for a better understanding of feed-forward anticipatory strategies.

View Article: PubMed Central - PubMed

Affiliation: Biomedical Technology Department, Found. Don C. Gnocchi Onlus, IRCCS, Via Capecelatro 66, 20148, Milan, Italy. gbonora@dongnocchi.it.

ABSTRACT

Background: Step climbing is a demanding task required for personal autonomy in daily living. Anticipatory Postural Adjustments (APAs) preceding gait initiation have been widely investigated revealing to be hypometric in Parkinson's disease (PD) with consequences in movement initiation. However, only few studies focused on APAs prior to step climbing. In this work, a novel method based on wearable inertial sensors for the analysis of APAs preceding gait initiation and step climbing was developed to further understand dynamic balance control. Validity and sensitivity of the method have been evaluated.

Methods: Eleven PD and 20 healthy subjects were asked to perform two transitional tasks from quiet standing to level walking, and to step climbing respectively. All the participants wore two inertial sensors, placed on the trunk (L2-L4) and laterally on the shank. In addition, a validation group composed of healthy subjects and 5 PD patients performed the tasks on two force platforms. Correlation between parameters from wearable sensors and force platforms was evaluated. Temporal parameters and trunk acceleration from PD and healthy subjects were analyzed.

Results: Significant correlation was found for the validation group between temporal parameters extracted from wearable sensors and force platforms and between medio-lateral component of trunk acceleration and correspondent COP displacement. These results support the validity of the method for evaluating APAs prior to both gait initiation and step climbing. Comparison between PD subjects and a subgroup of healthy controls confirms a reduction in PD of the medio-lateral acceleration of the trunk during the imbalance phase in the gait initiation task and shows similar trends during the imbalance and unloading phase of the step climbing task. Interestingly, PD subjects presented difficulties in adapting the medio-lateral amplitude of the imbalance phase to the specific task needs.

Conclusions: Validity of the method was confirmed by the significant correlation between parameters extracted from wearable sensors and force platforms. Sensitivity was proved by the capability to discriminate PD subjects from healthy controls. Our findings support the applicability of the method to subjects of different age. This method could be a possible valid instrument for a better understanding of feed-forward anticipatory strategies.

No MeSH data available.


Related in: MedlinePlus