Application of principal component analysis in vertical ground reaction force to discriminate normal and abnormal gait

A Mobile Gait Monitoring System for Abnormal Gait Diagnosis and Rehabilitation: A Pilot Study for Parkinson Disease Patients

Conventional gait rehabilitation treatment does not provide quantitative information on abnormal gait kinematics, and the match of the intervention strategy to the underlying clinical presentation may be limited by clinical expertise and experience. Also the effect of rehabilitation treatment may be reduced as the rehabilitation treatment is achieved only in a clinical setting. In this paper, a mobile gait monitoring system (MGMS) is proposed for the diagnosis of abnormal gait and rehabilitation. The proposed MGMS consists of Smart Shoes and a microsignal processor with a touch screen display. It monitors patients’ gait by observing the ground reaction force (GRF) and the center of GRF, and analyzes the gait abnormality. Since visual feedback about patients’ GRFs and normal GRF patterns are provided by the MGMS, patients can practice the rehabilitation treatment by trying to follow the normal GRF patterns without restriction of time and place. The gait abnormality proposed in this paper is defined by the deviation between the patient’s GRFs and normal GRF patterns, which are constructed as GRF bands. The effectiveness of the proposed gait analysis methods with the MGMS has been verified by preliminary trials with patients suffering from gait disorders.

Quantitative evaluation of the effects of subthalamic stimulation on gait in Parkinson's disease patients using principal component analysis

BACKGROUND

Principal component analysis (PCA) was applied to the ground reaction force (GRF) for evaluating the deep brain stimulation of the subthalamic nucleus (DBS-STN) effects in Parkinson's disease (PD) subjects with and without medication.

METHODS

Ten subjects who underwent DBS-STN were evaluated under the following four conditions: without treatment (mof-sof), with stimulation (mof-son), with medication (mon-sof), and with both treatments (mon-son). A control group of 30 subjects was also evaluated. PCA was applied separately on each GRF component. Broken stick criterion selected eight principal components (PC) from vertical GRF and one from each horizontal GRF. A standard distance was calculated using these 10 PCs and the gait speed to measure how far the PD group's gait was from the normal pattern.

RESULTS

The standard distance allowed classifying normal and PD subjects in the mof-sof condition with 100% accuracy, sensitivity, and specificity. The same distance was calculated for mon-sof, mof-son, and mon-son conditions. The smallest mean standard distance was found in the mon-son condition, which was significantly different from mof-sof (Friedman test with Dunn post-hoc, p < .05).

CONCLUSION

PCA allowed the quantitative evaluation of treatment effects, indicating that DBS-STN improves the GRF pattern in PD subjects, primarily in the medication on state.

Gait initiation evaluation after deep brain stimulation for Parkinson's disease: A 7-year follow-up

This study evaluated the long-term effects of deep brain stimulation of the subthalamic nucleus (DBS-STN) on gait initiation. Six Parkinson's disease (PD) patients who had undergone DBS-STN and 31 control subjects were evaluated. PD subjects were assessed at two different time periods: 11.3 ± 10.3 (P1) and 78.9 ± 10.6 (P2) months after surgery. Subjects under stimulation were tested in two conditions: without medication and with medication. Principal components (PC) analysis was separately applied on vertical, anterior-posterior and medial-lateral ground reaction force (GRF) from gait initiation, during the anticipatory postural adjustment (APA) phase. Three PC scores were chosen by the scree test for each GRF component. The higher loading factors pointed to major differences between controls and PD patients on maximum APA amplitude for vertical and anterior-posterior GRF. Friedman test showed a significant difference in standard distance among conditions (P = 0.006), with the post-hoc test recognizing differences only between P1 and P2 in the medication-on condition. All distances increased in the follow-up evaluation (P2), when considering the same medication condition, indicating a worsening in gait initiation after 7 years of follow-up.

Principal components of frequency domain electromyograms for muscular fatigue analysis

The parameters commonly employed for muscular fatigue (MF) analysis, the mean frequency (F(mean)) and median frequency (F(median)) of surface EMG (SEMG) spectra, did not present consistent results for exercises performed at low to moderate intensities. For overcoming this limitation, the present study proposes the use of principal component (PC) analysis of SEMG spectra for MF monitoring. The SEMG from vastus lateralis muscle of 24 young male subjects were recorded during a maximal effort test in cycle ergometer. Epochs of 200 ms SEMG, extracted from each period of muscle activation of each subject were used for estimating the amplitude spectra, which were employed to obtain the first two PCs. The PC coefficients from the first 40 spectra were used as a reference for calculating the standard distance. This index presented a consistent increase along the exercise, while the values of F(mean) and F(median) did not present any pattern. Comparisons between initial and final values from all subjects show no significant changes in F(mean) and F(median) (Student t test, P > 0.05) and a significant increase (P < 10(-3)) in standard distance, indicating this index as an alternative to MF analysis in cyclical exercises.