Fall Risk Assessment for the Elderly Based on Weak Foot Features of Wearable Plantar Pressure

Identifying changes in dynamic plantar pressure associated with radiological knee osteoarthritis based on machine learning and wearable devices

BACKGROUND

Knee osteoarthritis (KOA) is an irreversible degenerative disease that characterized by pain and abnormal gait. Radiography is typically used to detect KOA but has limitations. This study aimed to identify changes in plantar pressure that are associated with radiological knee osteoarthritis (ROA) and to validate them using machine learning algorithms.

METHODS

This study included 92 participants with variable degrees of KOA. A modified Kellgren-Lawrence scale was used to classify participants into non-ROA and ROA groups. The total feature set included 210 dynamic plantar pressure features captured by a wearable in-shoe system as well as age, gender, height, weight, and body mass index. Filter and wrapper methods identified the optimal features, which were used to train five types of machine learning classification models for further validation: k-nearest neighbors (KNN), support vector machine (SVM), random forest (RF), AdaBoost, and eXtreme gradient boosting (XGBoost).

RESULTS

Age, the standard deviation (SD) of the peak plantar pressure under the left lateral heel (f_L8PPP_std), the SD of the right second peak pressure (f_Rpeak2_std), and the SD of the variation in the anteroposterior displacement of center of pressure (COP) in the right foot (f_RYcopstd_std) were most associated with ROA. The RF model with an accuracy of 82.61% and F1 score of 0.8000 had the best generalization ability.

CONCLUSION

Changes in dynamic plantar pressure are promising mechanical biomarkers that distinguish between non-ROA and ROA. Combining a wearable in-shoe system with machine learning enables dynamic monitoring of KOA, which could help guide treatment plans.

Influence of motor capacity of the lower extremity and mobility performance on foot plantar pressures in community-dwelling older women

Objectives

To investigate the associations of motor capacity of the lower extremity and mobility performance in daily physical activities with peak foot plantar pressures during walking among older women.

Methods

Using the data collected among 58 community-dwelling older women (68.66 ± 3.85 years), Pearson correlation and multiple linear regression analyses were performed to analyze the associations of motor capacity of the lower extremity (the 30-s chair stand test, the timed one-leg stance with eyes closed, and the Fugl-Meyer assessment of lower extremity), mobility performance in daily physical activities (the average minutes of moderate to vigorous physical activity every day and the metabolic equivalents), and foot plantar pressures (peak force and peak pressure) with the age and body fat percentage as covariates.

Results

(1) The motor capacity of the lower extremity has higher explanatory power for peak foot plantar pressures compared with the mobility performance in daily physical activities. (2) Higher body fat percentage was positively associated with peak force and pressure, while a lower score on the Fugl-Meyer assessment of lower extremity was negatively associated with both of them. (3) The metabolic equivalents were positively associated with the peak force, while the 30-s chair stand test was negatively associated with it.

Conclusions

Mobility performance in daily physical activities can be significant predictors for peak foot plantar pressures among older women. The significant predictor variables include the Fugl-Meyer assessment of lower extremity, the 30-s chair stand test, and metabolic equivalents.

Identifying sensors-based parameters associated with fall risk in community-dwelling older adults: an investigation and interpretation of discriminatory parameters

BACKGROUND

Falls pose a severe threat to the health of older adults worldwide. Determining gait and kinematic parameters that are related to an increased risk of falls is essential for developing effective intervention and fall prevention strategies. This study aimed to investigate the discriminatory parameter, which lay an important basis for developing effective clinical screening tools for identifying high-fall-risk older adults.

METHODS

Forty-one individuals aged 65 years and above living in the community participated in this study. The older adults were classified as high-fall-risk and low-fall-risk individuals based on their BBS scores. The participants wore an inertial measurement unit (IMU) while conducting the Timed Up and Go (TUG) test. Simultaneously, a depth camera acquired images of the participants' movements during the experiment. After segmenting the data according to subtasks, 142 parameters were extracted from the sensor-based data. A t-test or Mann-Whitney U test was performed on the parameters for distinguishing older adults at high risk of falling. The logistic regression was used to further quantify the role of different parameters in identifying high-fall-risk individuals. Furthermore, we conducted an ablation experiment to explore the complementary information offered by the two sensors.

RESULTS

Fifteen participants were defined as high-fall-risk individuals, while twenty-six were defined as low-fall-risk individuals. 17 parameters were tested for significance with p-values less than 0.05. Some of these parameters, such as the usage of walking assistance, maximum angular velocity around the yaw axis during turn-to-sit, and step length, exhibit the greatest discriminatory abilities in identifying high-fall-risk individuals. Additionally, combining features from both devices for fall risk assessment resulted in a higher AUC of 0.882 compared to using each device separately.

CONCLUSIONS

Utilizing different types of sensors can offer more comprehensive information. Interpreting parameters to physiology provides deeper insights into the identification of high-fall-risk individuals. High-fall-risk individuals typically exhibited a cautious gait, such as larger step width and shorter step length during walking. Besides, we identified some abnormal gait patterns of high-fall-risk individuals compared to low-fall-risk individuals, such as less knee flexion and a tendency to tilt the pelvis forward during turning.

SFDA: Domain Adaptation With Source Subject Fusion Based on Multi-Source and Single-Target Fall Risk Assessment

In cross-subject fall risk classification based on plantar pressure, a challenge is that data from different subjects have significant individual information. Thus, the models with insufficient generalization ability can't perform well on new subjects, which limits their application in daily life. To solve this problem, domain adaptation methods are applied to reduce the gap between source and target domain. However, these methods focus on the distribution of the source and the target domain, but ignore the potential correlation among multiple source subjects, which deteriorates domain adaptation performance. In this paper, we proposed a novel method named domain adaptation with subject fusion (SFDA) for fall risk assessment, greatly improving the cross-subject assessment ability. Specifically, SFDA synchronously carries out source target adaptation and multiple source subject fusion by domain adversarial module to reduce source-target gap and distribution distance within source subjects of same class. Consequently, target samples can learn more task-specific features from source subjects to improve the generalization ability. Experiment results show that SFDA achieved mean accuracy of 79.17 % and 73.66 % based on two backbones in a cross-subject classification manner, outperforming the state-of-the-art methods on continuous plantar pressure dataset. This study proves the effectiveness of SFDA and provides a novel tool for implementing cross-subject and few-gait fall risk assessment.

Assessing Excessive Keratinization in Acral Areas through Dermatoscopy with Cross-Polarization and Parallel-Polarization: A Dermatoscopic Keratinization Scale

Excessive epidermal hyperkeratosis in acral areas is a common occurrence in dermatology practice, with a notable prevalence of approximately 65% in the elderly, especially in plantar lesions. Hyperkeratosis, characterized by thickening of the stratum corneum, can have various causes, including chronic physical or chemical factors, genetic predispositions, immunological disorders, and pharmaceutical compounds. This condition can significantly impact mobility, increase the risk of falls, and reduce the overall quality of life, particularly in older individuals. Management often involves creams containing urea to soften hyperkeratotic areas. Currently, subjective visual evaluation is the gold standard for assessing hyperkeratosis severity, lacking precision and consistency. Therefore, our research group proposes a novel 6-point keratinization scale based on dermatoscopy with cross-polarization and parallel-polarization techniques. This scale provides a structured framework for objective assessment, aiding in treatment selection, duration determination, and monitoring disease progression. Its clinical utility extends to various dermatological conditions involving hyperkeratosis, making it a valuable tool in dermatology practice. This standardized approach enhances communication among healthcare professionals, ultimately improving patient care and research comparability in dermatology.

Correlation between the foot pressure index and the prevalence of plantar hyperkeratosis

BACKGROUND

Plantar hyperkeratosis (HK) is a very prevalent foot lesion formed due to an alteration in the keratinisation process, thereby increasing keratynocites and accumulating multiple layers of the stratum corneum that leads to plantar pain. As foot shape and plantar pressures is related with their appearance, the aim of this study is to examine how foot posture and plantar pressure influence the appearance of this keratopathy.

MATERIAL AND METHODS

On a sample of 400 subjects (201 men and 199 women), the plantar pressures were evaluated by the Footscan® platform in 10 zones. The clinical exploration consisted in the valuation of the Foot Posture Index (FPI), and the assessment of the appeerance (and location) or not of plantar calluses or hyperkeratosis.

RESULTS

6.3% of the feet presented a highly supinated FPI, 15.5% were supinated, 57.3% corresponded to neutral, 17.3% were pronated and 3.8% were highly pronated. The participants with HK on the hallux, on the 1st, 2nd, 3rd or 5th MTH or on the lateral heel had a significantly higher pressure index (p < 0.001), ranging from 24.3 to 44% higher than those with no such alteration. Of the highly pronated feet, 66.7% presented HK in the hallux, while 32.3% of the supinated feet and 60% of the highly supinated feet presented it beneath the first MTH.

CONCLUSION

Foot posture influences the appearance of HK, though its association with plantar pressures. The participants with HK presented a mean foot pressure that was 32.3% higher than in those with no such condition. These values can be considered predictive for the appearance of HK and should be indicative of the need for preventive treatment.

Plantar pressure and falling risk in older individuals: a cross-sectional study

BACKGROUND

Falls are commonplace among elderly people. It is urgent to prevent falls. Previous studies have confirmed that there is a difference in plantar pressure between falls and non-falls in elderly people, but the relationship between fall risk and foot pressure has not been studied. In this study, the differences in dynamic plantar pressure between elderly people with high and low fall risk were preliminarily discussed, and the characteristic parameters of plantar pressure were determined.

METHODS

Twenty four high-fall-risk elderly individuals (HR) and 24 low-fall-risk elderly individuals (LR) were selected using the Berg Balance Scale 40 score. They wore wearable foot pressure devices to walk along a 20-m-long corridor. The peak pressure (PP), pressure time integral (PTI), pressure gradient (maximum pressure gradient (MaxPG), minimum pressure gradient (MinPG), full width at half maximum (FWHM)) and average pressure (AP) of their feet were measured for inter-group and intra-group analysis.

RESULTS

The foot pressure difference comparing the high fall risk with low fall risk groups was manifested in PP and MaxPG, concentrated in the midfoot and heel (p < 0.05), while the only time parameter, FWHM, was manifested in the whole foot (p < 0.05). The differences between the left and right foot were reflected in all parameters. The differences between the left and right foot in LR were mainly reflected in the heel (p < 0.05), while it in the HR was mainly reflected in the forefoot (p < 0.05).

CONCLUSIONS

The differences comparing the high fall risk with low fall risk groups were mostly reflected in the midfoot and heel. The HR may have been more cautious when landing. In the intra-group comparison, the difference between the right and left foot of the LR was mainly reflected during heel striking, while it was mainly reflected during pedalling in the HR. The sensitivity of PP, PTI and AP was lower and the newly introduced pressure gradient could better reflect the difference in foot pressure between the two groups. The pressure gradient can be used as a new foot pressure parameter in scientific research.

A Systematic Review of Wearable Sensor-Based Technologies for Fall Risk Assessment in Older Adults

Falls have been recognized as the major cause of accidental death and injury in people aged 65 and above. The timely prediction of fall risks can help identify older adults prone to falls and implement preventive interventions. Recent advancements in wearable sensor-based technologies and big data analysis have spurred the development of accurate, affordable, and easy-to-use approaches to fall risk assessment. The objective of this study was to systematically assess the current state of wearable sensor-based technologies for fall risk assessment among community-dwelling older adults. Twenty-five of 614 identified research articles were included in this review. A comprehensive comparison was conducted to evaluate these approaches from several perspectives. In general, these approaches provide an accurate and effective surrogate for fall risk assessment. The accuracy of fall risk prediction can be influenced by various factors such as sensor location, sensor type, features utilized, and data processing and modeling techniques. Features constructed from the raw signals are essential for predictive model development. However, more investigations are needed to identify distinct, clinically interpretable features and develop a general framework for fall risk assessment based on the integration of sensor technologies and data modeling.

Evaluation of the Foot Center of Pressure Estimation from Pressure Insoles during Sidestep Cuts, Runs and Walks

Estimating the foot center of pressure (CoP) position by pressure insoles appears to be an interesting technical solution to perform motion analysis beyond the force platforms surface area. The aim of this study was to estimate the CoP position from Moticon® pressure insoles during sidestep cuts, runs and walks. The CoP positions assessed from force platform data and from pressure insole data were compared. One calibration trial performed on the force platforms was used to localize the insoles in the reference coordinate system. The most accurate results were obtained when the motion performed during the calibration trial was similar to the motion under study. In such a case, mean accuracy of CoP position have been evaluated to 15±4mm along anteroposterior (AP) axis and 8.5±3mm along mediolateral (ML) axis for sidestep cuts, 18±5mm along AP axis and 7.3±4mm along ML axis for runs, 15±6mm along AP axis and 6.6±3mm along ML axis for walks. The accuracy of the CoP position assesment from pressure insole data increased with the vertical force applied to the pressure insole and with the number of pressure cells involved.