Long-term effects of automated mechanical peripheral stimulation on gait patterns of patients with Parkinson's disease

New treatments based on peripheral stimulation of the sensory–motor system have been inspiring new rehabilitation approaches in Parkinson’s disease (PD), especially to reduce gait impairment, levodopa washout effects, and the incidence of falls. The aim of this study was to evaluate the change in gait and the clinical status of PD patients after six sessions of a treatment based on automated mechanical peripheral stimulation (AMPS). Eighteen patients with PD and 15 age-matched healthy individuals (control group) participated in this study. A dedicated medical device delivered the AMPS. PD patients were treated with AMPS six times once every 4 days. All PD patients were treated in the off-levodopa phase and were evaluated with gait analysis before and after the first intervention (acute phase), after the sixth intervention, 48 h after the sixth intervention, and 10 days after the end of the treatment. To compare the differences among the AMPS interventions (pre, 6 AMPS, and 10 days) in terms of clinical scales, a t-test was used (α≤0.05). In addition, to compare the differences among the AMPS interventions (pre, post, 6 AMPS, 48 h and 10 days), the gait spatiotemporal parameters were analyzed using the Friedman test and the Bonferroni post-hoc test (α≤0.05). Also, for comparisons between the PD group and the control group, the gait spatiotemporal parameters were analyzed using the Mann–Whitney test and the Bonferroni post-hoc test (α≤0.05). The results of the study indicate that the AMPS treatment has a positive effect on bradykinesia because it improves walking velocity, has a positive effect on the step and stride length, and has a positive effect on walking stability, measured by the increase in stride length. These results are consistent with the improvements measured with clinical scales. These findings indicate that AMPS treatment seems to generate a more stable walking pattern in PD patients, reducing the well-known gait impairment that is typical of PD; regular repetition every 4 days of AMPS treatment appears to be able to improve gait parameters, to restore rhythmicity, and to reduce the risk of falls, with benefits maintained up to 10 days after the last treatment. The trial was registered online at ClinicalTrials.gov (number identifier: NCT0181528)

The impact of rheumatoid arthritis on foot function in the early stages of disease: a clinical case series

BACKGROUND Foot involvement occurs early in rheumatoid arthritis but the extent to which this impacts on the structure and function leading to impairment and foot related disability is unknown. The purpose of this study was to compare clinical disease activity, impairment, disability, and foot function in normal and early rheumatoid arthritis (RA) feet using standardised clinical measures and 3D gait analysis. METHODS Twelve RA patients with disease duration ≤2 years and 12 able-bodied adults matched for age and sex underwent 3D gait analysis to measure foot function. Disease impact was measured using the Leeds Foot impact Scale (LFIS) along with standard clinical measures of disease activity, pain and foot deformity. For this small sample, the mean differences between the groups and associated confidence intervals were calculated using the t distribution RESULTS Moderate-to-high foot impairment and related disability were detected amongst the RA patients. In comparison with age- and sex-matched controls, the patients with early RA walked slower (1.05 m/s Vs 1.30 m/s) and had a longer double-support phase (19.3% Vs 15.8%). In terminal stance, the heel rise angle was reduced in the patients in comparison with normal (-78.9° Vs -85.7°). Medial arch height was lower and peak eversion in stance greater in the RA patients. The peak ankle plantarflexion power profile was lower in the patients in comparison with the controls (3.4 W/kg Vs 4.6 W/kg). Pressure analysis indicated that the RA patients had a reduced lesser toe contact area (7.6 cm2 Vs 8.1 cm2), elevated peak forefoot pressure (672 kPa Vs 553 kPa) and a larger mid-foot contact area (24.6 cm2 Vs 19.4 cm2). CONCLUSION Analysis detected small but clinically important changes in foot function in a small cohort of RA patients with disease duration <2 years. These were accompanied by active joint disease and impairment and disability

Wearable Platform for Automatic Recognition of Parkinson Disease by Muscular Implication Monitoring

The need for diagnostic tools for the characterization of progressive movement disorders - as the Parkinson Disease (PD) - aiming to early detect and monitor the pathology is getting more and more impelling. The parallel request of wearable and wireless solutions, for the real-time monitoring in a non-controlled environment, has led to the implementation of a Quantitative Gait Analysis platform for the extraction of muscular implications features in ordinary motor action, such as gait. The here proposed platform is used for the quantification of PD symptoms. Addressing the wearable trend, the proposed architecture is able to define the real-time modulation of the muscular indexes by using 8 EMG wireless nodes positioned on lower limbs. The implemented system “translates” the acquisition in a 1-bit signal, exploiting a dynamic thresholding algorithm. The resulting 1-bit signals are used both to define muscular indexes both to drastically reduce the amount of data to be analyzed, preserving at the same time the muscular information. The overall architecture has been fully implemented on Altera Cyclone V FPGA. The system has been tested on 4 subjects: 2 affected by PD and 2 healthy subjects (control group). The experimental results highlight the validity of the proposed solution in Disease recognition and the outcomes match the clinical literature results

Wearable sensors system for an improved analysis of freezing of gait in Parkinson's disease using electromyography and inertial signals

We propose a wearable sensor system for automatic, continuous and ubiquitous analysis of Freezing of Gait (FOG), in patients affected by Parkinson's disease. FOG is an unpredictable gait disorder with different clinical manifestations, as the trembling and the shuffling-like phenotypes, whose underlying pathophysiology is not fully understood yet. Typical trembling-like subtype features are lack of postural adaptation and abrupt trunk inclination, which in general can increase the fall probability. The targets of this work are detecting the FOG episodes, distinguishing the phenotype and analyzing the muscle activity during and outside FOG, toward a deeper insight in the disorder pathophysiology and the assessment of the fall risk associated to the FOG subtype. To this aim, gyroscopes and surface electromyography integrated in wearable devices sense simultaneously movements and action potentials of antagonist leg muscles. Dedicated algorithms allow the timely detection of the FOG episode and, for the first time, the automatic distinction of the FOG phenotypes, which can enable associating a fall risk to the subtype. Thanks to the possibility of detecting muscles contractions and stretching exactly during FOG, a deeper insight into the pathophysiological underpinnings of the different phenotypes can be achieved, which is an innovative approach with respect to the state of art

Is the timed-up and go test feasible in mobile devices? A systematic review

The number of older adults is increasing worldwide, and it is expected that by 2050 over 2 billion individuals will be more than 60 years old. Older adults are exposed to numerous pathological problems such as Parkinson’s disease, amyotrophic lateral sclerosis, post-stroke, and orthopedic disturbances. Several physiotherapy methods that involve measurement of movements, such as the Timed-Up and Go test, can be done to support efficient and effective evaluation of pathological symptoms and promotion of health and well-being. In this systematic review, the authors aim to determine how the inertial sensors embedded in mobile devices are employed for the measurement of the different parameters involved in the Timed-Up and Go test. The main contribution of this paper consists of the identification of the different studies that utilize the sensors available in mobile devices for the measurement of the results of the Timed-Up and Go test. The results show that mobile devices embedded motion sensors can be used for these types of studies and the most commonly used sensors are the magnetometer, accelerometer, and gyroscope available in off-the-shelf smartphones. The features analyzed in this paper are categorized as quantitative, quantitative + statistic, dynamic balance, gait properties, state transitions, and raw statistics. These features utilize the accelerometer and gyroscope sensors and facilitate recognition of daily activities, accidents such as falling, some diseases, as well as the measurement of the subject's performance during the test execution.info:eu-repo/semantics/publishedVersio

Use of nonintrusive sensor-based information and communication technology for real-world evidence for clinical trials in dementia

Cognitive function is an important end point of treatments in dementia clinical trials. Measuring cognitive function by standardized tests, however, is biased toward highly constrained environments (such as hospitals) in selected samples. Patient-powered real-world evidence using information and communication technology devices, including environmental and wearable sensors, may help to overcome these limitations. This position paper describes current and novel information and communication technology devices and algorithms to monitor behavior and function in people with prodromal and manifest stages of dementia continuously, and discusses clinical, technological, ethical, regulatory, and user-centered requirements for collecting real-world evidence in future randomized controlled trials. Challenges of data safety, quality, and privacy and regulatory requirements need to be addressed by future smart sensor technologies. When these requirements are satisfied, these technologies will provide access to truly user relevant outcomes and broader cohorts of participants than currently sampled in clinical trials