Tom Chau

Upper limb prosthesis use and abandonment: A survey of the last 25 years

This review presents an analytical and comparative survey of upper limb prosthesis acceptance and abandonment as documented over the past 25 years, detailing areas of consumer dissatisfaction and ongoing technological advancements. English-language articles were identified in a search of Ovid, PubMed, and ISI Web of Science (1980 until February 2006) for key words upper limb and prosthesis. Articles focused on upper limb prostheses and addressing: (i) Factors associated with abandonment; (ii) Rejection rates; (iii) Functional analyses and patterns of wear; and (iv) Consumer satisfaction, were extracted with the exclusion of those detailing tools for outcome measurement, case studies, and medical procedures. Approximately 200 articles were included in the review process with 40 providing rates of prosthesis rejection. Quantitative measures of population characteristics, study methodology, and prostheses in use were extracted from each article. Mean rejection rates of 45% and 35% were observed in the literature for body-powered and electric prostheses respectively in pediatric populations. Significantly lower rates of rejection for both body-powered (26%) and electric (23%) devices were observed in adult populations while the average incidence of non-wear was similar for pediatric (16%) and adult (20%) populations. Documented rates of rejection exhibit a wide range of variance, possibly due to the heterogeneous samples involved and methodological differences between studies. Future research should comprise of controlled, multifactor studies adopting standardized outcome measures in order to promote comprehensive understanding of the factors affecting prosthesis use and abandonment. An enhanced understanding of these factors is needed to optimize prescription practices, guide design efforts, and satiate demand for evidence-based measures of intervention.

Short-Term Music Training Enhances Verbal Intelligence and Executive Function

Researchers have designed training methods that can be used to improve mental health and to test the efficacy of education programs. However, few studies have demonstrated broad transfer from such training to performance on untrained cognitive activities. Here we report the effects of two interactive computerized training programs developed for preschool children: one for music and one for visual art. After only 20 days of training, only children in the music group exhibited enhanced performance on a measure of verbal intelligence, with 90% of the sample showing this improvement. These improvements in verbal intelligence were positively correlated with changes in functional brain plasticity during an executive-function task. Our findings demonstrate that transfer of a high-level cognitive skill is possible in early childhood.

A review of analytical techniques for gait data. Part 1: fuzzy, statistical and fractal methods

In recent years, several new approaches to gait data analysis have been explored, including fuzzy systems, multivariate statistical techniques and fractal dynamics. Through a critical survey of recent gait studies, this paper reviews the potential of these methods to strengthen the gait laboratorys analytical arsenal. It is found that time-honoured multivariate statistical methods are the most widely applied and understood. Although initially promising, fuzzy and fractal analyses of gait data remain largely unknown and their full potential is yet to be realized. The trend towards fusing multiple techniques in a given analysis means that additional research into the application of these two methods will benefit gait data analysis.

Consumer design priorities for upper limb prosthetics

Purpose. To measure consumer satisfaction with upper limb prosthetics and provide an enumerated list of design priorities for future developments. Methods. A self-administered, anonymous survey collected information on participant demographics, history of and goals for prosthesis use, satisfaction, and design priorities. The questionnaire was available online and in paper format and was distributed through healthcare providers, community support groups, and one prosthesis manufacturer; 242 participants of all ages and levels of upper limb absence completed the survey. Results. Rates of rejection for myoelectric hands, passive hands, and body-powered hooks were 39%, 53%, and 50%, respectively. Prosthesis wearers were generally satisfied with their devices while prosthesis rejecters were dissatisfied. Reduced prosthesis weight emerged as the highest priority design concern of consumers. Lower cost ranked within the top five design priorities for adult wearers of all device types. Life-like appearance is a priority for passive/cosmetic prostheses, while improved harness comfort, wrist movement, grip control and strength are required for body-powered devices. Glove durability, lack of sensory feedback, and poor dexterity were also identified as design priorities for electric devices. Conclusions. Design priorities reflect consumer goals for prosthesis use and vary depending on the type of prosthesis used and age. Future design efforts should focus on the development of more light-weight, comfortable prostheses.

A review of analytical techniques for gait data. Part 2: neural network and wavelet methods

Multivariate gait data have traditionally been challenging to analyze. Part 1 of this review explored applications of fuzzy, multivariate statistical and fractal methods to gait data analysis. Part 2 extends this critical review to the applications of artificial neural networks and wavelets to gait data analysis. The review concludes with a practical guide to the selection of alternative gait data analysis methods. Neural networks are found to be the most prevalent non-traditional methodology for gait data analysis in the last 10 years. Interpretation of multiple gait signal interactions and quantitative comparisons of gait waveforms are identified as important data analysis topics in need of further research.

Upper-limb prosthetics: critical factors in device abandonment.

Biddiss E, Chau T: Upper-limb prosthetics: critical factors in device abandonment. Am J Phys Med Rehabil 2007;86:977–987. Objective:To investigate the roles of predisposing characteristics, established need, and enabling resources in upper-limb prosthesis use and abandonment. Design:A self-administered, anonymous survey was designed to explore these factors. The questionnaire was available online and in paper format and was distributed through healthcare providers, community support groups, and one prosthesis manufacturer. Two hundred forty-two participants of all ages and levels of upper-limb absence completed the survey. Results:Of participants, 20% had abandoned prosthesis use. Predisposing factors, namely, origin of limb absence, gender, bilateral limb absence, and, most importantly, level of limb absence, proved influential in the decision not to wear prostheses. Enabling resources such as the availability of health care, cost, and quality of training did not weigh heavily on prosthesis rejection, with the exception of the fitting time frame and the involvement of clients in the prosthesis selection. Conversely, the state of available technology was a highly censured factor in abandonment, specifically in the areas of comfort and function. Perceived need emerged as a predominant factor in prosthesis use. Conclusions:Future research should focus on continued development of more comfortable and functional prostheses, particularly for individuals with high-level or bilateral limb absence. Improved follow-up, repair, and information services, together with active involvement of clients in the selection of prostheses meeting their specific goals and needs, is recommended.

Decoding subjective preference from single-trial near-infrared spectroscopy signals

Near-infrared spectroscopy (NIRS) has recently been identified as a safe, portable and relatively low-cost signal acquisition tool for non-invasive brain-computer interface (BCI) development. The ultimate goal of BCI research is for the user to be able to communicate functional intent directly through thoughts. In this paper we propose an NIRS-BCI paradigm based on directly decoding neural correlates of decision making, specifically subjective preference evaluation. Nine subjects were asked to mentally evaluate two possible drinks and decide which they preferred. Frequency domain near-infrared spectroscopy was used to image each subjects prefrontal cortex during the task. Using mean signal amplitudes as features and linear discriminant analysis, we were able to decode which drink was preferred on a single-trial basis with an average accuracy of 80%.

Real-Time Classification of Forearm Electromyographic Signals Corresponding to User-Selected Intentional Movements for Multifunction Prosthesis Control

Pattern recognition-based multifunction prosthesis control strategies have largely been demonstrated with subsets of typical able-bodied hand movements. These movements are often unnatural to the amputee, necessitating significant user training and do not maximally exploit the potential of residual muscle activity. This paper presents a real-time electromyography (EMG) classifier of user-selected intentional movements rather than an imposed subset of standard movements. EMG signals were recorded from the forearm extensor and flexor muscles of seven able-bodied participants and one congenital amputee. Participants freely selected and labeled their own muscle contractions through a unique training protocol. Signals were parameterized by the natural logarithm of root mean square values, calculated within 0.2 s sliding and non overlapping windows. The feature space was segmented using fuzzy C-means clustering. With only 2 min of training data from each user, the classifier discriminated four different movements with an average accuracy of 92.7% plusmn 3.2%. This accuracy could be further increased with additional training data and improved user proficiency that comes with practice. The proposed method may facilitate the development of dynamic upper extremity prosthesis control strategies using arbitrary, user-preferred muscle contractions.

Classification of prefrontal activity due to mental arithmetic and music imagery using hidden Markov models and frequency domain near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) has recently been investigated as a non-invasive brain-computer interface (BCI). In particular, previous research has shown that NIRS signals recorded from the motor cortex during left- and right-hand imagery can be distinguished, providing a basis for a two-choice NIRS-BCI. In this study, we investigated the feasibility of an alternative two-choice NIRS-BCI paradigm based on the classification of prefrontal activity due to two cognitive tasks, specifically mental arithmetic and music imagery. Deploying a dual-wavelength frequency domain near-infrared spectrometer, we interrogated nine sites around the frontopolar locations (International 10-20 System) while ten able-bodied adults performed mental arithmetic and music imagery within a synchronous shape-matching paradigm. With the 18 filtered AC signals, we created task- and subject-specific maximum likelihood classifiers using hidden Markov models. Mental arithmetic and music imagery were classified with an average accuracy of 77.2% +/- 7.0 across participants, with all participants significantly exceeding chance accuracies. The results suggest the potential of a two-choice NIRS-BCI based on cognitive rather than motor tasks.

A Review of Emerging Access Technologies for Individuals With Severe Motor Impairments

Research and development in the field of access technologies for individuals with severe motor impairments has accelerated over the past 10 years. Many emergent alternatives to conventional mechanical switches, such as infrared sensing, electromyography, oculography, and computer vision, have been investigated for those retaining some limited volitional motor ability. At the same time, electroencephalography, electrocorticography, intracortical recordings, and electro-dermal activity have been explored for those presenting as locked in. The relevant literature is scattered across many disciplines, obfuscating the strength of the clinical evidence in support of the different access technologies currently in development. This article systematically organizes the literature on the aforementioned access technologies, summarizing their underlying operational mechanisms while reviewing the clinical evidence reported between 1996 and 2006. Research evidence within this period is generally found to be at the case study or uncontrolled study level, with very modest sample sizes. Novel mechanical switches and electroencephalography-based access systems dominate the literature, whereas many other movement-based access modalities have emerged with promising early findings. Access methods for those without extant physical movement constitute a critical direction for future and ongoing research efforts.