Finally getting to objectively diagnosing your walking deficits, without that your therapist is just guessing what needs to be corrected. My PT told me to 'walk this way'. That was completely and totally fucking useless. But they did cherry pick participants so more research needed.
Validation of IMU-based gait event detection during curved walking and turning in older adults and Parkinson’s Disease patients
Journal of NeuroEngineering and Rehabilitation volume 18, Article number: 28 (2021)
Abstract
Background
Identification of individual gait events is essential for clinical gait analysis, because it can be used for diagnostic purposes or tracking disease progression in neurological diseases such as Parkinson’s disease. Previous research has shown that gait events can be detected from a shank-mounted inertial measurement unit (IMU), however detection performance was often evaluated only from straight-line walking. For use in daily life, the detection performance needs to be evaluated in curved walking and turning as well as in single-task and dual-task conditions.
Methods
Participants (older adults, people with Parkinson’s disease, or people who had suffered from a stroke) performed three different walking trials: (1) straight-line walking, (2) slalom walking, (3) Stroop-and-walk trial. An optical motion capture system was used a reference system. Markers were attached to the heel and toe regions of the shoe, and participants wore IMUs on the lateral sides of both shanks. The angular velocity of the shank IMUs was used to detect instances of initial foot contact (IC) and final foot contact (FC), which were compared to reference values obtained from the marker trajectories.
Results
The detection method showed high recall, precision and F1 scores in different populations for both initial contacts and final contacts during straight-line walking (IC: recall
89%).
Conclusions
Shank-mounted IMUs can be used to detect gait events during straight-line walking, slalom walking and turning. However, more false events were observed during turning and more events were missed during turning. For use in daily life we recommend identifying turning before extracting temporal gait parameters from identified gait events.
Background
Gait is recognized as a surrogate marker of health, and provides essential clinical insights in neurological disease status [1, 2]. Traditionally, gait has been assessed by visual observation, which suffers from subjectivity and imprecision [3]. To overcome these limitations, multi-camera optical motion capture (OMC) systems can be used, but these systems are relatively expensive and restricted to expertise laboratories [4]. Furthermore, there is increasing evidence that the gait pattern observed in clinical gait assessments does not reflect daily-life gait [5, 6]. Hence, to get a more complete picture of health status, there is an increasing demand for methods that allow for long-term gait monitoring in ambulatory settings. Inertial measurement units (IMUs) provide a promising alternative to assess gait in an objective, unobtrusive and unconstrained manner [4, 7].
The term “gait” refers to “the way of walking” [8, 9] and human gait is commonly segmented into repetitive gait cycles. A normal gait cycle begins and ends with initial contact (IC), the instance when the foot strikes the ground [10]. The time interval between two consecutive ICs of the same foot is referred to as the gait cycle time or stride time. The time interval between two successive ICs of the opposite feet is called the step time. If, additionally, the event of final foot contact (FC) is considered, then all phases in the gait cycle can be described: swing and stance phase, or single and double support phase [1, 10]. Identification of gait events (GEs) and phases is considered essential for clinical gait assessment [8]. GEs can be detected from a single low back-mounted IMU [11,12,13,14,15,16], however findings suggest that detecting GEs is easier from shank- or foot-mounted IMUs [17,18,19] where foot-mounted IMUs increase errors, especially in pathological gait patterns [19, 20].
The performance of IMU-based GE detection is, however, often tested only with treadmill walking [12, 14] or from walking trials where only the straight-line segments of walking trajectories were included in the analysis [13, 17, 21]. For more complex walking tasks, such as slalom walking or dual-task walking, one often relies on visually counting of the number of steps, which does not allow to assess the time error of the GE detection and is more prone to errors. Whether IMU-based GE detection is still valid in more complex walking tasks is yet to be shown. Daily-life gait is likely influenced by obstacle negotiation (approximately 30% of daily-life gait is spent along curved trajectories [22, 23]) and dual-/multi-tasking [5].
The aim of this study is therefore to quantify the performance of IC and FC detection in straight-line walking under single-task and dual-task conditions, and to quantify detection performance in curved walking and turning in (healthy) older adults (OA), people diagnosed with Parkinson’s disease (PD), and people who have suffered from a stroke (ST).
Methods
A step was considered as the interval between consecutive ICs of the ipsi- and contralateral foot [10], and corresponding to forward displacement of the foot together with a forward displacement of the trunk [24]. A stride was the interval between two consecutive ICs of the same foot, and as such it was equivalent to the gait cycle and every stride consisted of two steps [8, 10].
Study population
Three different groups were distinguished: (1) OAs with no signs of any movement disorders, (2) PD participants in the medication ON state, and (3) ST participants (Table 1). For the OAs the minimum age was 60 years. All participants needed to be able to walk independently with or without walking aids. Exclusion criteria were a high fall risk (i.e. > 2 falls in the last month, as reported by the participant), any impairment that refrained the participant from giving consent to participate in the study, and a score below 20 for the Montreal Cognitive Assessment (MoCA) [25]. All participants gave written informed consent and the study was approved by the ethical committee of the medical faculty at University Hospital Schleswig-Holstein (UKSH), No: D438/18.
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