Inertial Sensor-Based Motion Analysis of Lower Limbs for Rehabilitation Treatments

Ankle rehabilitation robot training for stroke patients with foot drop: Optimizing intensity and frequency

BACKGROUND

Robotic solutions for ankle joint physical therapy have extensively been researched. The optimal frequency and intensity of training for patients when using the ankle robot is not known which can affect rehabilitation outcome.

OBJECTIVE

To explore the optimal ankle robot training protocol on foot drop in stroke subjects.

METHODS

Subjects were randomly divided into four groups, with 9 in each group. The subjects received different intensities (low or high intensity) with frequencies (1 session/day or 2 sessions/day) of robot combination training. Each session lasted 20 minutes and all subjects were trained 5 days a week for 3 weeks.

RESULTS

After 3 weeks of treatment, all groups showed an improvement in passive and active ankle dorsiflexion range of motion (PROM and AROM) and Fugl-Meyer Assessment for lower extremity (FMA-LE) compared to pre-treatment. When training at the same level of intensity, patients who received 2 sessions/day of training had better improvement in ankle dorsiflexion PROM than those who received 1 session/day. In terms of the improvement in dorsiflexion AROM and FMA-LE, patients who received 2 sessions/day with high intensity training improved better than other protocols.

CONCLUSION

High frequency and high intensity robot training can be more effective in improving ankle dysfunction.

Kinematics-Based Lower Limb Rehabilitation Monitoring Following Partial Knee Meniscectomy: Case Study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022;2022:2531-2534. [PMID: 36086092 DOI: 10.1109/embc48229.2022.9871925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Physiotherapy includes treatment to restore and optimize mobility after surgery, injury, disease, and/or degeneration. Based on assessments throughout the recovery process from visual observations of movement, exercises are prescribed to perform at home between clinic sessions. Although technical advances have facilitated remote communication between therapists and patients, accurate assessment of at-home exercises is challenged by a lack of direct observation. The current study advances remote assessment tools to assess key lower body exercises prescribed in a case study following recovery from arthroscopic partial meniscectomy (APM). Using Vicon motion capture, recovery metrics related to range of motion, strength, and gait function were extracted. Peak knee flexion angle on the operated leg during heel slide increased from 91.61° ± 4.17° to 127.42° ± 2.35° (p<0.05), although significant differences were found compared to the non-operated leg at Day 6 (138.19° ± 5.44°, p<0.05). Repetition times in heel slide and leg raise exercises on the affected leg decreased from Day 2 (2.74s) to Day 6 (1.07s), indicating strength recovery. Step length asymmetry decreased by 61.22% and step width asymmetry decreased by 41.75% from Day 2 to Day 6 post surgery, demonstrating improved gait function. This work presents a sample of automated recovery metrics that can be used for therapists to assess rehabilitation and inform the recovery process. Implications of the study findings on remote assessment using wearables are discussed. This work presents kinematics based quantifiable lower limb rehabilitation metrics to assess recovery objectives (e.g., knee flexion angle to assess knee range of motion) used by clinicians to inform recovery remotely.

The Relationship between Leg Extension Angle at Late Stance and Knee Flexion Angle at Swing Phase during Gait in Community-Dwelling Older Adults

This study aimed to clarify the relationship between leg extension angle and knee flexion angle during gait in older adults. The subjects of this cross-sectional study were 588 community-dwelling older adults (74.6 ± 6.1 y). Segment angles and acceleration were measured using five inertial measurement units during comfortable gait, and bilateral knee and hip joint angles, and leg extension angle, reflecting whole lower limb extension at late stance, were calculated. Propulsion force was estimated using the increase in velocity calculated from anterior acceleration of the sacrum during late stance. Correlation analysis showed that leg extension angle was associated with knee flexion angle at swing phase and hip extension angle and increase in velocity at late stance (r = 0.444–508, p < 0.001). Multiple regression analysis showed that knee flexion angle at mid-swing was more affected by leg extension angle (β = 0.296, p < 0.001) than by gait speed (β = 0.219, p < 0.001) and maximum hip extension angle (β = −0.150, p < 0.001). These findings indicate that leg extension angle may be a meaningful parameter for improving gait function in older adults due to the association with knee kinematics during swing as well as propulsion force at late stance.

INERTIAL SENSOR-BASED MOTION ANALYSIS SYSTEM OF BRIDGE-STYLE MOVEMENT FOR REHABILITATION TREATMENTS

In the clinical course of the treatment, impartial representation of the patients’ rehabilitation state is a necessary condition for taking the best treatment to match the state of the current recovery. Bridge-style movement is one of the earliest training programs of the bed position change and is also the basis of successful standing and walking training because the bridge-style movement can inhibit the spasticity pattern of lower limb extensors and improve the control and coordination ability from the pelvis to lower limb. However, patients’ bridge-style movement planning for the current rehabilitation state largely depends on therapists’ clinical experience and subjective that may deteriorate the rehabilitation effect. Thus, it is necessary for hemiplegic patients to develop quantitative motor function assessment to judge its current rehabilitation state. This paper proposes a quantitative evaluating method to detect patients’ bridge-style movement posture and analyze their motion abilities. The real-time postural change of the bridge-style movement can be acquired by the inertial sensors attached to the waist, thigh, and crus. The bridge-style movement process of patients is recorded and analyzed by the software processing program. Finally, the experiment can be carried out to verify the feasibility and correctness of the evaluation method. The experimental results show that the evaluation method can judge patients’ current motion ability and rehabilitation state. And it is helpful for therapists to carry out targeted training for patients’ state.

Ankle Angle Prediction Using a Footwear Pressure Sensor and a Machine Learning Technique

Ankle injuries may adversely increase the risk of injury to the joints of the lower extremity and can lead to various impairments in workplaces. The purpose of this study was to predict the ankle angles by developing a footwear pressure sensor and utilizing a machine learning technique. The footwear sensor was composed of six FSRs (force sensing resistors), a microcontroller and a Bluetooth LE chipset in a flexible substrate. Twenty-six subjects were tested in squat and stoop motions, which are common positions utilized when lifting objects from the floor and pose distinct risks to the lifter. The kNN (k-nearest neighbor) machine learning algorithm was used to create a representative model to predict the ankle angles. For the validation, a commercial IMU (inertial measurement unit) sensor system was used. The results showed that the proposed footwear pressure sensor could predict the ankle angles at more than 93% accuracy for squat and 87% accuracy for stoop motions. This study confirmed that the proposed plantar sensor system is a promising tool for the prediction of ankle angles and thus may be used to prevent potential injuries while lifting objects in workplaces.

Determining anatomical frames via inertial motion capture: A survey of methods

Despite the exponential growth in using inertial measurement units (IMUs) for biomechanical studies, future growth in "inertial motion capture" is stymied by a fundamental challenge - how to estimate the orientation of underlying bony anatomy using skin-mounted IMUs. This challenge is of paramount importance given the need to deduce the orientation of the bony anatomy to estimate joint angles. This paper systematically surveys a large number (N = 112) of studies from 2000 to 2018 that employ four broad categories of methods to address this challenge across a range of body segments and joints. We categorize these methods as: (1) Assumed Alignment methods, (2) Functional Alignment methods, (3) Model Based methods, and (4) Augmented Data methods. Assumed Alignment methods, which are simple and commonly used, require the researcher to visually align the IMU sense axes with the underlying anatomical axes. Functional Alignment methods, also commonly used, relax the need for visual alignment but require the subject to complete prescribed movements. Model Based methods further relax the need for prescribed movements but instead assume a model for the joint. Finally, Augmented Data methods shed all of the above assumptions, but require data from additional sensors. Significantly different estimates of the underlying anatomical axes arise both across and within these categories, and to a degree that renders it difficult, if not impossible, to compare results across studies. Consequently, a significant future need remains for creating and adopting a standard for defining anatomical axes via inertial motion capture to fully realize this technology's potential for biomechanical studies.

High density muscle size and muscle power are associated with both gait and sit-to-stand kinematic parameters in frail nonagenarians

Frailty is an important concept in clinical and demographic research in the elderly because of its incidence level and its relationship with adverse outcomes. Functional ability declines with advanced age, likely due to changes in muscle function. This study aimed to examine the relationship between muscle quality and muscle power with kinematics from functional tests in a population of 21 institutionalized frail nonagenarian (91.3 ± 3.1 years). Here, muscle quality was measured by segmenting areas of high- and low-density fibers with computerized tomography. In addition, muscle strength and muscle power were obtained through maximal strength and power tests using resistance exercises. Finally, functional capacity outcomes (i.e., balance, gait velocity and sit-to-stand ability), as well as kinematic parameters, were evaluated from a tri-axial sensor used during a battery of functional tests. Our results show that lower limb muscle quality, maximal strength and power output present statistically significant relationships with different kinematic parameters, especially during the sit-to-stand and gait tests (e.g. leg power and maximum power during sit-to-stand (r = 0.80) as well as quadriceps muscle mass and step asymmetry (r = -0,71). In particular, frail individuals with greater muscle quality needed less trunk range of motion to make the transition between sitting and standing, took less time to stand up, and exerted a major peak power of force. As a conclusion, a loss of muscle quality and power may lead to motor control impairments such as gait, sit-to-stand and balance that can be the cause of adverse events such as falls.

Lower extremity outcome measures: considerations for clinical trials in spinal cord injury

STUDY DESIGN

This is a focused review article.

OBJECTIVES

To identify important concepts in lower extremity (LE) assessment with a focus on locomotor outcomes and provide guidance on how existing outcome measurement tools may be best used to assess experimental therapies in spinal cord injury (SCI). The emphasis lies on LE outcomes in individuals with complete and incomplete SCI in Phase II-III trials.

METHODS

This review includes a summary of topics discussed during a workshop focusing on LE function in SCI, conceptual discussion of corresponding outcome measures and additional focused literature review.

RESULTS

There are a number of sensitive, accurate, and responsive outcome tools measuring both quantitative and qualitative aspects of LE function. However, in trials with individuals with very acute injuries, a baseline assessment of the primary (or secondary) LE outcome measure is often not feasible.

CONCLUSION

There is no single outcome measure to assess all individuals with SCI that can be used to monitor changes in LE function regardless of severity and level of injury. Surrogate markers have to be used to assess LE function in individuals with severe SCI. However, it is generally agreed that a direct measurement of the performance for an appropriate functional activity supersedes any surrogate marker. LE assessments have to be refined so they can be used across all time points after SCI, regardless of the level or severity of spinal injury.

SPONSORS

Craig H. Neilsen Foundation, Spinal Cord Outcomes Partnership Endeavor.

Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation

Capturing hand motions for hand function evaluations is essential in the medical field. Various data gloves have been developed for rehabilitation and manual dexterity assessments. This study proposed a modular data glove with 9-axis inertial measurement units (IMUs) to obtain static and dynamic parameters during hand function evaluation. A sensor fusion algorithm is used to calculate the range of motion of joints. The data glove is designed to have low cost, easy wearability, and high reliability. Owing to the modular design, the IMU board is independent and extensible and can be used with various microcontrollers to realize more medical applications. This design greatly enhances the stability and maintainability of the glove.