Freezing of gait and fall detection in Parkinson’s disease using wearable sensors: a systematic review

Abstract

Despite the large number of studies that have investigated the use of wearable sensors to detect gait disturbances such as Freezing of gait (FOG) and falls, there is little consensus regarding appropriate methodologies for how to optimally apply such devices. Here, an overview of the use of wearable systems to assess FOG and falls in Parkinson’s disease (PD) and validation performance is presented. A systematic search in the PubMed and Web of Science databases was performed using a group of concept key words. The final search was performed in January 2017, and articles were selected based upon a set of eligibility criteria. In total, 27 articles were selected. Of those, 23 related to FOG and 4 to falls. FOG studies were performed in either laboratory or home settings, with sample sizes ranging from 1 PD up to 48 PD presenting Hoehn and Yahr stage from 2 to 4. The shin was the most common sensor location and accelerometer was the most frequently used sensor type. Validity measures ranged from 73–100% for sensitivity and 67–100% for specificity. Falls and fall risk studies were all home-based, including samples sizes of 1 PD up to 107 PD, mostly using one sensor containing accelerometers, worn at various body locations. Despite the promising validation initiatives reported in these studies, they were all performed in relatively small sample sizes, and there was a significant variability in outcomes measured and results reported. Given these limitations, the validation of sensor-derived assessments of PD features would benefit from more focused research efforts, increased collaboration among researchers, aligning data collection protocols, and sharing data sets.

Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: a mixed-methods systematic review

“…This systematic review, like several before [70, 74–78], highlights a need to further investigate the clinimetric properties of the measures derived from wearables, to improve standardization of data protocols, variable definitions, and to encourage further development of patient-specific algorithms. The possible benefit of using multimodal information needs to be further investigated.…”

Wearables for independent living in older adults: Gait and falls

“…Recent reviews have examined wearable type, placement/location, algorithms and gait outcomes across a range of cohorts [23, [34][35][36]. In general author's remark on the heterogeneity of wearables, algorithms and gait outcomes due to a general lack of standardisation which make it difficult to compare and contrast across studies.…”

Home‐Based Monitoring of Falls Using Wearable Sensors in Parkinson's Disease

“…Such sensors can potentially detect falls automatically, quantitatively, and, importantly, continuously in the patient's own environment, thus providing an attractive alternative to self‐reported burdensome and unreliable diaries. Some promising examples of the use of wearable sensors to quantify fall events in controlled settings and free‐living environments were reported in PD . Moreover, sensors can be used together with a personal emergency response system built into the sensor box, thus providing patients with rapid access to emergency assistance, if needed, for example, when they experience difficulty rising after a fall…”

“…Some promising examples of the use of wearable sensors to quantify fall events in controlled settings and free-living environments were reported in PD. 17,18 Moreover, sensors can be used together with a personal emergency response system built into the sensor box, thus providing patients with rapid access to emergency assistance, if needed, for example, when they experience difficulty rising after a fall. 19 In this study, we analyzed data from such a personal emergency response system in a large cohort of elderly participants who used a single wearable falls detector, worn as a necklace, to collect fall events in their own home environment.…”