A smart insole system capable of identifying proper heel raise posture for chronic ankle instability rehabilitation

Dynamic Foot Pressure During Walking: A Potential Indicator of Bone Mineral Density

BACKGROUND

Physical skeletal loading can affect the bone mineral density (BMD). This study investigated the association between BMD and dynamic foot pressure during gait.

METHODS

A total of 104 patients (mean age, 62.6 ± 12.4 years; 23 male and 81 female) who underwent dual x-ray absorptiometry and pedobarography were included. BMD values of the lumbar spine, femoral neck, and total femur were assessed. The mean and maximum pressures were measured at the hallux, lesser toes, 1st metatarsal head, 2nd and 3rd metatarsal heads, 4th and 5th metatarsal heads, midfoot, medial heel, and lateral heel. Multivariable regression analysis was performed to identify factors significantly associated with BMD.

RESULTS

The lumbar spine BMD was significantly associated with the mean pressure at the 4th and 5th metatarsal heads (p = 0.041, adjusted R 2 of model = 0.081). The femoral neck BMD was significantly associated with the maximum pressure at the 2nd and 3rd metatarsal heads (p = 0.002, adjusted R 2 = 0.213). The total femoral BMD also showed a significant association with the maximum pressure at the 2nd and 3rd metatarsal heads (p = 0.003, adjusted R 2 = 0.360).

CONCLUSIONS

Foot plantar pressure during gait was significantly associated with BMD, and could potentially be used to predict the presence of osteoporosis.

LEVEL OF EVIDENCE

Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis

BACKGROUND

The relationship between physical function, musculoskeletal disorders and sarcopenia is intricate. Current physical function tests, such as the gait speed test and the chair stand test, have limitations in eliminating subjective influences. To overcome this, smart devices utilizing inertial measurement unit sensors and artificial intelligence (AI)-based methods are being developed.

METHODS

We employed cutting-edge technologies, including the smart insole device and pose estimation based on AI, along with three classification models: random forest (RF), support vector machine and artificial neural network, to classify control and sarcopenia groups. Patient data of 83 individuals were divided into train and test sets, with approximately 67% allocated for training. Classification models were implemented using RStudio, considering individual and combined variables obtained through pose estimation and smart insole measurements.

RESULTS

Performance evaluation of the classification models utilized accuracy, precision, recall and F1-score indicators. Using only pose estimation variables, accuracy ranged from 0.92 to 0.96, with F1-scores of 0.94-0.97. Key variables identified by the RF model were 'Hip_dif', 'Ankle_dif' and 'Hipankle_dif'. Combining variables from both methods increased accuracy to 0.80-1.00, with F1-scores of 0.73-1.00.

CONCLUSIONS

In our study, a classification model that integrates smart insole and pose estimation technology was assessed. The RF model showed impressive results, particularly in the case of the Hip and Ankle variables. The growth of advanced measurement technologies suggests a promising avenue for identifying and utilizing additional digital biomarkers in the management of various disorders. The convergence of AI technologies with diagnostics and treatment approaches a promising future for enhanced interventions in conditions like sarcopenia.

Effects of textured insoles and elastic braces on dynamic stability in patients with functional ankle instability

BACKGROUND

Functional ankle instability (FAI) is a common condition that affects individuals who have experienced previous ankle sprains. Textured insoles and elastic ankle braces have been previously used as interventions to improve stability in FAI patients. However, the optimal combination of these interventions has not been fully explored. The objective of this study was to investigate the effects of different types of textured insoles and elastic ankle braces on the dynamic stability of individuals diagnosed with FAI.

METHODS

The study involved 18 FAI patients who performed single-leg landing tasks with and without wearing an eight-band elastic ankle brace while wearing textured insoles with protrusion heights of 0 mm, 1 mm, and 2 mm. The dynamic posture stability index (DPSI) and its components in the anterior-posterior (APSI), mediolateral (MLSI) and vertical (VSI) directions were calculated from the ground reaction force collected from the Kistler force plate during the first three seconds of the landing tasks.

RESULTS

A significant interaction was found between textured insole type and ankle brace for DPSI (P = 0.026), APSI (P = 0.001), and VSI (P = 0.021). However, no significant interaction was observed for MLSI (P = 0.555). With elastic ankle braces, textured insoles with 1-mm protrusions significantly enhanced anterior-posterior, mediolateral, vertical, and overall stability compared to textured insoles with no and 2 mm protrusions (P < 0.05). Without elastic ankle braces, textured insoles with 1-mm protrusions significantly improved the anterior-posterior (P = 0.012) and overall stability (P = 0.014) of FAI patients compared to smooth insoles.

CONCLUSIONS

The combination of textured insoles with 1-mm protrusion heights and an elastic ankle brace could enhance the dynamic stability of individuals with FAI, potentially mitigating the risk of ankle sprains.

A Novel Tilted-Plane Ergometer System for Subject-Specific Rehabilitation

Immobilization due to various reasons can lead to disuse muscle atrophy. If prolonged, the circumstance is exacerbated and may lead to joint contracture, dysfunction, and long-term sequela. Thus, a balanced exercise regimen is crucial. While able-bodied individuals can perform a variety of exercises, bedridden patients typically resort to exercising primarily with bicycle ergometers. However, since the pedaling trajectory with ergometers is confined to the sagittal plane, muscles responsible for medial-lateral movement and balance are not effectively trained. Furthermore, the direction of joint reaction forces, which is crucial for specific patients with ligament injuries, recurrent dislocations, and medial osteoarthritis, is not well facilitated. Thus, it would be beneficial for patients without full body weight support ability to train ab-/ad-ductor muscles by altering the direction of extrinsic load via ergometers. In this study, we present a novel Tilted-Plane Ergometer and proof-of-concept experiment with one healthy subject. The results suggest that subtle changes in ergometer configurations lead to different movements, joint alignments, and muscle recruitment patterns.

Assessing physical abilities of sarcopenia patients using gait analysis and smart insole for development of digital biomarker

The aim of this study is to compare variable importance across multiple measurement tools, and to use smart insole and artificial intelligence (AI) gait analysis to create variables that can evaluate the physical abilities of sarcopenia patients. By analyzing and comparing sarcopenia patients with non sarcopenia patients, this study aims to develop predictive and classification models for sarcopenia and discover digital biomarkers. The researchers used smart insole equipment to collect plantar pressure data from 83 patients, and a smart phone to collect video data for pose estimation. A Mann-Whitney U was conducted to compare the sarcopenia group of 23 patients and the control group of 60 patients. Smart insole and pose estimation were used to compare the physical abilities of sarcopenia patients with a control group. Analysis of joint point variables showed significant differences in 12 out of 15 variables, but not in knee mean, ankle range, and hip range. These findings suggest that digital biomarkers can be used to differentiate sarcopenia patients from the normal population with improved accuracy. This study compared musculoskeletal disorder patients to sarcopenia patients using smart insole and pose estimation. Multiple measurement methods are important for accurate sarcopenia diagnosis and digital technology has potential for improving diagnosis and treatment.