Walking is a central activity of daily life, and there is an increasing demand for objective measurement-based gait assessment. In contrast to stationary systems, wearable inertial measurement units (IMUs) have the potential to enable non-restrictive and accurate gait assessment in daily life. We propose a set of algorithms that uses the measurements of two foot-worn IMUs to determine major spatiotemporal gait parameters that are essential for clinical gait assessment: durations of five gait phases for each side as well as stride length, walking speed, and cadence. Compared to many existing methods, the proposed algorithms neither require magnetometers nor a precise mounting of the sensor or dedicated calibration movements. They are therefore suitable for unsupervised use by non-experts in indoor as well as outdoor environments. While previously proposed methods are rarely validated in pathological gait, we evaluate the accuracy of the proposed algorithms on a very broad dataset consisting of 215 trials and three different subject groups walking on a treadmill: healthy subjects (n = 39), walking at three different speeds, as well as orthopedic (n = 62) and neurological (n = 36) patients, walking at a self-selected speed. The results show a very strong correlation of all gait parameters (Pearson's r between 0.83 and 0.99, p < 0.01) between the IMU system and the reference system. The mean absolute difference (MAD) is 1.4 % for the gait phase durations, 1.7 cm for the stride length, 0.04 km/h for the walking speed, and 0.7 steps/min for the cadence. We show that the proposed methods achieve high accuracy not only for a large range of walking speeds but also in pathological gait as it occurs in orthopedic and neurological diseases. In contrast to all previous research, we present calibration-free methods for the estimation of gait phases and spatiotemporal parameters and validate them in a large number of patients with different pathologies. The proposed methods lay the foundation for ubiquitous unsupervised gait assessment in daily-life environments.
Demographic changes associated with an expanding and aging population will lead to an increasing number of orthopedic surgeries, such as joint replacements. To support patients’ home exercise programs after total hip replacement and completing subsequent inpatient rehabilitation, a low-cost, smartphone-based augmented reality training game (TG) was developed. To evaluate its motion detection accuracy, data from 30 healthy participants were recorded while using the TG. A 3D motion analysis system served as reference. The TG showed differences of 18.03 mm to 24.98 mm along the anatomical axes. Surveying the main movement direction of the implemented exercises (squats, step-ups, side-steps), differences between 10.13 mm to 24.59 mm were measured. In summary, the accuracy of the TG’s motion detection is sufficient for use in exergames and to quantify progress in patients’ performance. Considering the findings of this study, the presented exer-game approach has potential as a low-cost, easily accessible support for patients in their home exercise program.
Background New technologies, for example, telerehabilitation (TR) tools, can support physiotherapists’ work. Even though studies have demonstrated their potential, TR is not yet fully implemented in Austrian outpatient physiotherapy. As a result of the Coronavirus pandemic and the associated lockdowns, physiotherapists in Austria were confronted with the challenge of offering therapies without physical contact. This study aims to investigate opinions and experiences of physiotherapists in Austria regarding TR and its implementation in different clinical fields. Methods A qualitative research design with expert interviews and a focus group discussion were conducted. Data were analysed using content analysis. The categories were formed following a deductive-inductive approach. Results The interview partners considered opportunities for using synchronous TR in internal medicine as well as orthopaedics and traumatology, especially in later, exercise-dominated stages. In addition, using TR can be supportive for patient education. In the field of neurology, synchronous TR is viewed with some criticism, especially when used for people with severe neuropsychological disorders. Asynchronous TR is considered useful across all disciplines and could support physical therapy from the first therapy session and throughout the treatment. Important questions regarding liability, billing, or data protection still need to be clarified. Interdisciplinary approaches in TR should also be pursued to improve care. Conclusion The use of asynchronous TR in addition to regular physiotherapy is seen as promising in all clinical fields. In general, when implementing TR, the needs and requirements of different fields should be considered. Moreover, various framework conditions still need to be clarified for further implementation of TR.
Background Early detection of cognitive impairment can slow progression to dementia when using appropriate therapy. For early detection of dementia dual task combining cognitive tasks and walking might be suitable, since individuals with cognitive impairment have shown greater changes in gait specific parameters on dual task test (DT) compared to single task test (ST). This study investigates whether these changes correlate with poorer cognitive function in healthy older adults. Methods In a cross-sectional study 174 healthy adults (66,48±4,26years; 40%female) completed the Cognitive Functions Dementia Test (CFD), with a lower CFD index indicating lower cognitive function. Participants performed ST (walking 20m) and DT (walking 20m & counting backwards), in which step frequency, stride length and gait speed were monitored by Pablo sensors. Cognitive cost (CC) was determined for each gait variable. CC represents a change score between SD & DT and quantifies cognitive demands, with higher CC indicating poorer cognitive function. Pearson correlations and stepwise linear regression adjusted for age and gender were applied to analyze the association between CFD Index (dependent variable) and CC gate variables (predictors) (α = 5%). Results Significant correlations were observed between CFD Index and CC step frequency (p=.014, r=-.187), CC stride length (p=.037, r=-.160) and CC gait speed (p=.002, r=-.232). Since gait variables were intercorrelated (multicollinearity), only gait speed was significant predictor for CFD Index (ß = -.243, p<.001, R2 = .053) in a stepwise adjusted regression model. Conclusions Changes in gait speed might be sensitive enough to indicate differences of cognitive performance among older individuals. Therefore, DT could be included in screening procedures as alert for potential cognitive decline. Key messages
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