Validity of Instrumented Insoles for Step Counting, Posture and Activity Recognition: A Systematic Review

Abstract

With the growing interest in daily activity monitoring, several insole designs have been developed to identify postures, detect activities, and count steps. However, the validity of these devices is not clearly established. The aim of this systematic review was to synthesize the available information on the criterion validity of instrumented insoles in detecting postures activities and steps. The literature search through six databases led to 33 articles that met inclusion criteria. These studies evaluated 17 different insole models and involved 290 participants from 16 to 75 years old. Criterion validity was assessed using six statistical indicators. For posture and activity recognition, accuracy varied from 75.0% to 100%, precision from 65.8% to 100%, specificity from 98.1% to 100%, sensitivity from 73.0% to 100%, and identification rate from 66.2% to 100%. For step counting, accuracies were very high (94.8% to 100%). Across studies, different postures and activities were assessed using different criterion validity indicators, leading to heterogeneous results. Instrumented insoles appeared to be highly accurate for steps counting. However, measurement properties were variable for posture and activity recognition. These findings call for a standardized methodology to investigate the measurement properties of such devices.

Wearable Solutions for Patients with Parkinson’s Disease and Neurocognitive Disorder: A Systematic Review

“…These insoles can extract gait features and help in classification of PD stages and in daily monitoring for rehabilitation purposes. The results of the comparative study [34] emphasize that the data validity of smart insoles is 75% to 100% accurate, 75% to 100% precise, and the specificity lies between 73% to 100%. In this way, we can say that smart wearables [40] allow quantitative, objective, and reliable evaluation of motor activities.…”

“…Not all the aforementioned devices in [27][28][29][30][31][32][33] are appropriate for daily routines in people with Parkinson's disorder, and it is hard to find a single wearable device for diagnosis, monitoring, and rehabilitation of PD. A systematic review in [34] provided a potential solution for continuous and unobstructed appraisal of Parkinson's patients that resides in smart insoles.…”

A Review of Internet of Things Technologies for Ambient Assisted Living Environments

“…Banknote identifier [84] Difficult to use, complex user input Prosthetic Damping Control [85] Manual control required, low comfortability, high complexity Toto Intelligence Toilet II [86] Over-complexity, difficult to use Head driven mouse for smartwatch [87] Low practicality, high learning curve Smart armchair [88] Low usefulness, complex to adjust and control Home Automation Kit for smart home control [89] High complexity, difficult to use Smart insoles [90] Low reliability Garmin Vivofit activity tracker [91] Low usability, high learning curve…”

Workplace activity classification from shoe-based movement sensors

“…toe protection and slip resistance, a sensor built into these shoes would be a practical and relatively easily implementable solution in an occupational setting. Previous work has shown that an accelerometer placed on a shoe has similar accuracy in predicting activities as other placements [ 6 ], but the performance of shoe based sensors have not been evaluated in a free-living setting previously [ 7 ].…”