The aim of this review paper is to summarize recent developments in the field of wearable sensors and systems that are relevant to the field of rehabilitation. The growing body of work focused on the application of wearable technology to monitor older adults and subjects with chronic conditions in the home and community settings justifies the emphasis of this review paper on summarizing clinical applications of wearable technology currently undergoing assessment rather than describing the development of new wearable sensors and systems. A short description of key enabling technologies (i.e. sensor technology, communication technology, and data analysis techniques) that have allowed researchers to implement wearable systems is followed by a detailed description of major areas of application of wearable technology. Applications described in this review paper include those that focus on health and wellness, safety, home rehabilitation, assessment of treatment efficacy, and early detection of disorders. The integration of wearable and ambient sensors is discussed in the context of achieving home monitoring of older adults and subjects with chronic conditions. Future work required to advance the field toward clinical deployment of wearable sensors and systems is discussed.

Background: Virtual reality (VR) technology along with treadmill training (TT) can effectively provide goal-oriented practice and promote improved motor learning in patients with neurological disorders. Moreover, the VR + TT scheme may enhance cognitive engagement for more effective gait rehabilitation and greater transfer to over ground walking. For this purpose, we developed an individualized treadmill controller with a novel speed estimation scheme using swing foot velocity, which can enable user-driven treadmill walking (UDW) to more closely simulate over ground walking (OGW) during treadmill training. OGW involves a cyclic acceleration-deceleration profile of pelvic velocity that contrasts with typical treadmill-driven walking (TDW), which constrains a person to walk at a preset constant speed. In this study, we investigated the effects of the proposed speed adaptation controller by analyzing the gait kinematics of UDW and TDW, which were compared to those of OGW at three pre-determined velocities. Methods: Ten healthy subjects were asked to walk in each mode (TDW, UDW, and OGW) at three pre-determined speeds (0.5 m/s, 1.0 m/s, and 1.5 m/s) with real time feedback provided through visual displays. Temporal-spatial gait data and 3D pelvic kinematics were analyzed and comparisons were made between UDW on a treadmill, TDW, and OGW. Results: The observed step length, cadence, and walk ratio defined as the ratio of stride length to cadence were not significantly different between UDW and TDW. Additionally, the average magnitude of pelvic acceleration peak values along the anterior-posterior direction for each step and the associated standard deviations (variability) were not significantly different between the two modalities. The differences between OGW and UDW and TDW were mainly in swing time and cadence, as have been reported previously. Also, step lengths between OGW and TDW were different for 0.5 m/s and 1.5 m/s gait velocities, and walk ratio between OGS and UDW was different for 1.0 m/s gait velocities. Conclusions: Our treadmill control scheme implements similar gait biomechanics of TDW, which has been used for repetitive gait training in a small and constrained space as well as controlled and safe environments. These results reveal that users can walk as stably during UDW as TDW and employ similar strategies to maintain walking speed in both UDW and TDW. Furthermore, since UDW can allow a user to actively participate in the virtual reality (VR) applications with variable walking velocity, it can induce more cognitive activities during the training with VR, which may enhance motor learning effects.

This paper presents the framework for developing a robotic system to improve accuracy and reliability of clinical assessment. Clinical assessment of spasticity tends to have poor reliability because of the nature of the in-person assessment. To improve accuracy and reliability of spasticity assessment, a haptic device, named the HESS (Haptic Elbow Spasticity Simulator) has been designed and constructed to recreate the clinical “feel” of elbow spasticity based on quantitative measurements. A mathematical model representing the spastic elbow joint was proposed based on clinical assessment using the Modified Ashworth Scale (MAS) and quantitative data (position, velocity, and torque) collected on subjects with elbow spasticity. Four haptic models (HMs) were created to represent the haptic feel of MAS 1, 1+, 2, and 3. The four HMs were assessed by experienced clinicians; three clinicians performed both in-person and haptic assessments, and had 100% agreement in MAS scores; and eight clinicians who were experienced with MAS assessed the four HMs without receiving any training prior to the test. Inter-rater reliability among the eight clinicians had substantial agreement (). The eight clinicians also rated the level of realism (7.63 0.92 out of 10) as compared to their experience with real patients.

This paper introduces transparency-optimized control architectures (TOCAs) using two communication channels. Two classes of two-channel TOCAs are found, thereby showing that two channels are sufficient to achieve transparency. These TOCAs achieve a greater level of transparency but poorer stability than three-channel TOCAs and four-channel TOCAs. Stability of the two-channel TOCAs has been enhanced while minimizing transparency degradation by adding a filter; and a combined use of the two classes of two-channel TOCAs is proposed for both free space and constrained motion, which involve switching between two TOCAs for transition between free space and constrained motions. The stability condition of the switched teleoperation system is derived for practical applications. Through the one degree-of-freedom (DOF) experiment, the proposed two-channel TOCAs were shown to operate stably, while achieving better transparency under time delay than the other TOCAs.

Glabridin is a polyphenolic compound with reported anti-inflammatory and anti-oxidative effects. In the previous study, we synthesized glabridin derivatives—HSG4112, (S)-HSG4112, and HGR4113—based on the structure–activity relationship study of glabridin to improve its biological efficacy and chemical stability. In the present study, we investigated the anti-inflammatory effects of the glabridin derivatives in lipopolysaccharide (LPS)-stimulated RAW264.7 macrophages. We found that the synthetic glabridin derivatives significantly and dose-dependently suppressed the production of nitric oxide (NO) and prostaglandin E2 (PGE2), and decreased the level of inducible nitric oxygen synthase (iNOS) and cyclooxygenase-2 (COX-2) and the expression of pro-inflammatory cytokines interleukin-1β (IL-1β), IL-6, and tumor necrosis factor alpha (TNF-α). The synthetic glabridin derivatives inhibited the nuclear translocation of the NF-κB by inhibiting phosphorylation of the inhibitor of κB alpha (IκB-α), and distinctively inhibited the phosphorylation of ERK, JNK, and p38 MAPKs. In addition, the compounds increased the expression of antioxidant protein heme oxygenase (HO-1) by inducing nuclear translocation of nuclear factor erythroid 2-related factor 2 (Nrf2) through ERK and p38 MAPKs. Taken together, these results indicate that the synthetic glabridin derivatives exert strong anti-inflammatory effects in LPS-stimulated macrophages through MAPKs and NF-κB pathways, and support their development as potential therapeutics against inflammatory diseases.

Individuals with cerebral palsy have neurological deficits that may interfere with motor function and lead to abnormal walking patterns. It is important to know the joint moment generated by the patient's muscles during walking in order to assist the suboptimal gait patterns. In this paper, we describe a practical strategy for estimating the internal moment of a knee joint from surface electromyography (sEMG) and knee joint angle measurements. This strategy requires only isokinetic knee flexion and extension tests to obtain a relationship between the sEMG and the knee internal moment, and it does not necessitate comprehensive laboratory calibration, which typically requires a 3-D motion capture system and ground reaction force plates. Four estimation models were considered based on different assumptions about the functions of the relevant muscles during the isokinetic tests and the stance phase of walking. The performance of the four models was evaluated by comparing the estimated moments with the gold standard internal moment calculated from inverse dynamics. The results indicate that an optimal estimation model can be chosen based on the degree of cocontraction. The estimation error of the chosen model is acceptable (normalized root-mean-squared error: 0.15-0.29, R: 0.71-0.93) compared to previous studies (Doorenbosch and Harlaar, 2003; Doorenbosch and Harlaar, 2004; Doorenbosch, Joosten, and Harlaar, 2005), and this strategy provides a simple and effective solution for estimating knee joint moment from sEMG.