Myoelectric control of prosthetic hands: state-of-the-art review

[Prediction of speech understanding with the transcutaneous partially implantable bone conduction hearing system Osia®. German Version]

BACKGROUND

The active transcutaneous, partially implantable osseointegrated bone conduction system Cochlear™ Osia® (Cochlear, Sydney, Australia) has been approved for use in German-speaking countries since April 2021. The Osia is indicated for patients with conductive (CHL) or mixed hearing loss (MHL) with an average bone conduction (BC) hearing loss of 55 dB or less, or with single-sided deafness (SSD).

OBJECTIVES

The aim of this retrospective study was to investigate the prediction of postoperative speech recognition with Osia and to evaluate the speech recognition of patients with MHL and an aided dynamic range of less than 30 dB with Osia.

MATERIALS AND METHODS

Between 2017 and 2022, 29 adult patients were fitted with the Osia, 10 patients (11 ears) with CHL and 19 patients (21 ears) with MHL. MHL was subdivided into two groups: MHL‑I with four-frequency pure-tone average in BC (BC-4PTA) ≥ 20 dB HL and < 40 dB HL (n = 15 patients; 20 ears) vs. MHL-II with BC-4PTA ≥ 40 dB HL (n = 4 patients; 5 ears). All patients tested a bone conduction hearing device on a softband preoperatively. Speech intelligibility in quiet was assessed preoperatively using the Freiburg monosyllabic test unaided and with the test system and postoperatively with Osia. The maximum monosyllabic score (mEV) unaided and the monosyllabic score with the test system at 65 dB SPL were correlated with the postoperative monosyllabic score with Osia at 65 dB SPL.

RESULTS

Preoperative prediction of postoperative outcome with Osia was better using the mEV than the EV at 65 dB SPL with the test device on the softband. Postoperative EV was most predictive for patients with CHL and least predictive for patients with mixed hearing loss with 4PTA BC ≥ 40 dB HL. For the test device at softband, results tended to show the minimum achievable outcome and the mEV tended to predict the realistically achievable outcome.

CONCLUSION

Osia can be used for the treatment of CHL and MHL within the indication limits. The average preoperative bone conduction hearing threshold also provides an approximate estimate of the postoperative EV with Osia, for which the most accurate prediction is obtained using the preoperative mEV. Prediction accuracy decreases from a BC-4PTA of ≥ 40 dB.

Prediction of postoperative speech comprehension with the transcutaneous partially implantable bone conduction hearing system Osia®

BACKGROUND

The active transcutaneous, partially implantable osseointegrated bone conduction system Cochlear™ Osia® (Cochlear, Sydney, Australia) has been approved for use in German-speaking countries since April 2021. The Osia is indicated for patients either having conductive (CHL) or mixed hearing loss (MHL) with an average bone conduction (BC) hearing loss of 55 dB HL or less, or having single-sided deafness (SSD).

OBJECTIVES

The aim of this retrospective study was to investigate the prediction of postoperative speech recognition with Osia® and to evaluate the speech recognition of patients with MHL and in particular an aided dynamic range of less than 30 dB with Osia®.

MATERIALS AND METHODS

Between 2017 and 2022, 29 adult patients were fitted with the Osia®, 10 patients (11 ears) with CHL and 19 patients (25 ears) with MHL. MHL was subdivided into two groups: MHL‑I with four-frequency pure-tone average in BC (BC-4PTA) ≥ 20 dB HL and < 40 dB HL (n = 15 patients; 20 ears) vs. MHL-II with BC-4PTA ≥ 40 dB HL (n = 4 patients; 5 ears). All patients tested a bone conduction hearing device on a softband preoperatively. Speech intelligibility in quiet was assessed preoperatively using the Freiburg monosyllabic test in unaided condition, with the trial BCHD preoperatively and with Osia® postoperatively with Osia®. The maximum word recognition score (mWRS) unaided and the word recognition score (WRS) with the test system at 65 dB SPL were correlated with the postoperative WRS with Osia® at 65 dB SPL.

RESULTS

Preoperative prediction of postoperative outcome with Osia® was better using the mWRS than by the WRS at 65 dB SPL with the test device on the softband. Postoperative WRS was most predictive for patients with CHL and less predictable for patients with mixed hearing loss with BC-4PTA ≥ 40 dB HL. For the test device on a softband, the achievable outcome tended to a minimum, with the mWRS tending to predict the realistically achievable outcome.

CONCLUSION

Osia® can be used for the treatment of CHL and MHL within the indication limits. The average preoperative bone conduction hearing threshold also provides an approximate estimate of the postoperative WRS with Osia®, for which the most accurate prediction is obtained using the preoperative mWRS. Prediction accuracy decreases from a BC-4PTA of ≥ 40 dB HL.

Aligning US Agency Policies for Cardiovascular Devices Through the Breakthrough Devices Program

Importance

The US Food and Drug Administration (FDA) and Centers for Medicare & Medicaid Services (CMS) have different statutory authorities; FDA evaluates safety and effectiveness for market authorization of medical devices while CMS determines whether coverage is "reasonable and necessary" for its beneficiaries. CMS has recently enacted policies automatically providing supplemental reimbursement for new, costly devices authorized after designation in FDA's Breakthrough Devices Program (BDP) and in June 2023 issued notice for a new Transitional Coverage for Emerging Technologies pathway, accelerating coverage for Breakthrough devices.

Observations

Aiming to incentivize innovation, FDA awards Breakthrough designations early in device development to expedite market authorization and can accept greater uncertainty in benefit and risk, contingent on postmarket evidence generation. Since 2020, Breakthrough designation has effectively automatically qualified devices to receive supplemental Medicare reimbursement after CMS waived a long-standing requirement that devices demonstrate "substantial clinical improvement" for beneficiaries. Using publicly available information, 3 examples of cardiovascular devices illustrate that the BDP may allow for FDA authorization based on less rigorous evidence, such as single-arm trials focused on surrogate end points with short-term follow-up whose participants are often not representative of Medicare beneficiaries. In 1 case, Breakthrough designation allowed a 30% decrease in enrollment of a trial used to support approval. Initial positive findings for some devices have remained unverified, and in 1 case even partially nullified, by postmarket studies. Manufacturers have also used Breakthrough designations to set the price of devices to facilitate additional pass-through payments, leading to higher short-term and long-term costs to CMS and health care systems.

Conclusions and Relevance

The BDP may qualify new, costly devices for higher and automatic Medicare reimbursement despite evidence not being representative of CMS beneficiaries and persistent uncertainty of benefit and risk. To ensure the best evidence is generated to inform clinical care, FDA could apply more selectivity to BDP eligibility, specify objective criteria for revoking Breakthrough designation when appropriate, and ensure timely postmarket evidence generation, whereas CMS could independently review clinical evidence, advise manufacturers about standards for coverage review, and make supplemental payments and long-term device reimbursement contingent on clinical outcome benefit and postmarket evidence generation.

Ranking Decision-Making Criteria for Early Adoption of Innovative Surgical Technologies

Importance

There is no decision-making framework in the early-adoption stage of novel surgical technologies, putting the quality of health care and resource allocation of the health care system at risk.

Objective

To investigate relevant weighted criteria that decision-makers may use to make an informed decision for the early adoption of innovative surgical technologies.

Design, Setting, and Participants

This multi-institutional decision analytical modeling study used a mixed-methods multicriteria decision analysis (MCDA) and had 2 phases. First, a panel of 12 experts validated decision criteria in the literature and identified additional criteria. Second, 33 Canadian experts prioritized the main criteria (domains) using the composition pairwise-comparison weight-elicitation method (analytical hierarchy process model) and ranked their subcriteria using the direct-ranking elicitation method (Likert scale). Data were analyzed, and response consistency was estimated using the consistency ratio. Analysis of variance was used to assess for significant differences between expert responses. The MCDA was conducted at McGill University between 2021 and 2023. Data were collected nationally by inviting experts in Canada.

Main Outcome and Measure

Criteria domain weights and subcriteria rankings. Priority vectors, which are priority scores analyzed and prioritized from expert responses, were used to rank criteria domains and subcriteria for decision-making on adopting new innovative surgical technologies.

Results

A total of 45 experts (33 male [73.3%] and 12 female [26.7%]) were invited with different levels of education (22 experts with MD or equivalent, 13 experts with master's degree, and 12 experts with PhD degree) and years of experience (4 experts with <10, 12 experts with 11-20, 18 experts with 21-30, and 11 experts with >30 years). Surgeon experts (23 individuals) were from all surgical disciplines, and nonsurgeon experts (22 individuals) were administrative officers in surgical device procurement, health technology assessment experts, and hospital directors. A total of 7 domains and 44 subcriteria were identified. The MCDA model found that clinical outcomes had the highest priority vector, at 0.429, followed by patients and public relevance (0.135). Hospital-specific criteria (priority vector, 0.099), technology-specific criteria (priority vector, 0.092), and physician-specific criteria (priority vector, 0.087) were the next most highly ranked. The lowest priority vectors were for economic criteria, at 0.083, and finally policies and procedures, at 0.075. There was consensus in the responses (consistency ratio = 0.006), and there were no statistically significant differences between expert responses.

Conclusions and relevance

This study weighted priority criteria domains in importance and established ranked subcriteria for decision-making of early adoption of surgical technologies. Putting these criteria into a framework may help surgeons and decision-makers make informed decisions for the early adoption of new surgical technologies.

Midline Compared With Peripheral Intravenous Catheters for Therapy of 4 Days or Longer in Pediatric Patients: A Randomized Clinical Trial

Importance

Peripheral intravenous catheters (PIVCs) frequently fail during treatment causing therapy interruption, pain, recatheterization, and additional health care costs. Midline catheters (MCs) may improve functional dwell time and reduce failure compared with traditional PIVCs.

Objective

To compare device failure of MCs with PIVCs.

Design, Setting, and Participants

This was a pragmatic, randomized clinical superiority trial with an embedded internal pilot study conducted from July 2020 to May 2022. The study took place in a quaternary pediatric hospital in Brisbane, Queensland, Australia. Inclusion criteria were patients aged 1 to 18 years requiring peripherally compatible intravenous therapy for 4 days or longer.

Interventions

Patients were randomly assigned 1:1 to receive a PIVC or MC, stratified by age (≤5 years, >5 years). One catheter was studied per patient.

Main Outcomes and Measures

The primary outcome was all-cause device failure, defined as premature cessation of device function. Secondary outcomes included number of insertion attempts, insertion failure, pain (on insertion), procedural time, patient/parent satisfaction (with insertion), device dwell time, device complications during dwell time, additional vascular access devices required to complete treatment, clinician satisfaction (at removal), and health care costs.

Results

Of the 128 patients randomly assigned to study groups, 127 patients (median [IQR] age, 7 [2-13] years; 71 male [56%]) had a device inserted, with 65 (51.2%) in the PIVC group and 62 (48.8%) in the MC group. All patients were included in the intention-to-treat analysis. Device failure was lower in patients in the MC group (10 [16.1%]) compared with those in the PIVC group (30 [46.2%]; odds ratio [OR], 0.22; 95% CI, 0.10-0.52; P <.001). MCs were associated with fewer insertion attempts (mean difference [MD], -0.3; 95% CI, -0.5 to 0; P = .04), increased dwell time (MD, 66.9 hours; 95% CI, 36.2-97.5 hours; P <.001), and fewer patients required additional vascular access devices to complete treatment in the MC group (4 [6.5%]) and PIVC group (19 [29.2%]; OR, 0.17; 95% CI, 0.05-0.52; P = .002). Compared with PIVCs, use of MCs was associated with greater patient (9.0 vs 7.1 of 10; P = .002) and parent (9.1 vs 8.2 of 10; P = .02) satisfaction and lower health care costs (AUS -$151.67 [US -$101.13] per person; 95% credible interval, AUS -$171.45 to -$131.90 [US -$114.20 to -$87.95]).

Conclusions and Relevance

Findings suggest that MC insertion for patients requiring peripherally compatible intravenous therapy for 4 days or longer should be prioritized to reduce the resource intensive, expensive, and burdensome sequelae of device failure.

Trial Registration

Australia New Zealand Clinical Trials Registry, ACTRN12620000724976.

Evaluation of feature projection techniques in object grasp classification using electromyogram signals from different limb positions

A myoelectric prosthesis is manipulated using electromyogram (EMG) signals from the existing muscles for performing the activities of daily living. A feature vector that is formed by concatenating data from many EMG channels may result in a high dimensional space, which may cause prolonged computation time, redundancy, and irrelevant information. We evaluated feature projection techniques, namely principal component analysis (PCA), linear discriminant analysis (LDA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and spectral regression extreme learning machine (SRELM), applied to object grasp classification. These represent feature projections that are combinations of either linear or nonlinear, and supervised or unsupervised types. All pairs of the four types of feature projection with seven types of classifiers were evaluated, with data from six EMG channels and an IMU sensors for nine upper limb positions in the transverse plane. The results showed that SRELM outperformed LDA with supervised feature projections, and t-SNE was superior to PCA with unsupervised feature projections. The classification errors from SRELM and t-SNE paired with the seven classifiers were from 1.50% to 2.65% and from 1.27% to 17.15%, respectively. A one-way ANOVA test revealed no statistically significant difference by classifier type when using the SRELM projection, which is a nonlinear supervised feature projection (p = 0.334). On the other hand, we have to carefully select an appropriate classifier for use with t-SNE, which is a nonlinear unsupervised feature projection. We achieved the lowest classification error 1.27% using t-SNE paired with a k-nearest neighbors classifier. For SRELM, the lowest 1.50% classification error was obtained when paired with a neural network classifier.

Solving musculoskeletal biomechanics with machine learning

Deep learning is a relatively new computational technique for the description of the musculoskeletal dynamics. The experimental relationships of muscle geometry in different postures are the high-dimensional spatial transformations that can be approximated by relatively simple functions, which opens the opportunity for machine learning (ML) applications. In this study, we challenged general ML algorithms with the problem of approximating the posture-dependent moment arm and muscle length relationships of the human arm and hand muscles. We used two types of algorithms, light gradient boosting machine (LGB) and fully connected artificial neural network (ANN) solving the wrapping kinematics of 33 muscles spanning up to six degrees of freedom (DOF) each for the arm and hand model with 18 DOFs. The input-output training and testing datasets, where joint angles were the input and the muscle length and moment arms were the output, were generated by our previous phenomenological model based on the autogenerated polynomial structures. Both models achieved a similar level of errors: ANN model errors were 0.08 ± 0.05% for muscle lengths and 0.53 ± 0.29% for moment arms, and LGB model made similar errors-0.18 ± 0.06% and 0.13 ± 0.07%, respectively. LGB model reached the training goal with only 103 samples, while ANN required 106 samples; however, LGB models were about 39 times slower than ANN models in the evaluation. The sufficient performance of developed models demonstrates the future applicability of ML for musculoskeletal transformations in a variety of applications, such as in advanced powered prosthetics.

Optical methods for quantitative and label-free sensing in living human tissues: principles, techniques, and applications

We present an overview of quantitative and label-free optical methods used to characterize living biological tissues, with an emphasis on emerging applications in clinical tissue diagnostics. Specifically, this review focuses on diffuse optical spectroscopy, imaging, and tomography, optical coherence-based techniques, and non-linear optical methods for molecular imaging. The potential for non- or minimally-invasive assessment, quantitative diagnostics, and continuous monitoring enabled by these tissue-optics technologies provides significant promise for continued clinical translation.